Table of contents

THE PROCEEDING OF THE 4^TH INTERNATIONAL CONFERENCE ON COMPUTING AND APPLIED INFORMATICS 2019

On behalf of the Organizing Committee, I am pleased to present to you the Proceeding of the 4th International Conference on Computing and Applied Informatics. This is the fourth event of the conference series organized by The Faculty of Computer Science and Information Technology, Universitas Sumatera Utara. We are honored to accept 133 outstanding works from authors from 7 different countries. Each paper has been through a challenging review process, and we would like to appreciate each of the authors that able to cooperate during the process in order to ensure the quality of each paper. With the acceptance rate of 45%, it is unfortunate for us to see that some high-quality manuscripts did not manage to go through the review process. Nevertheless, please accept our highest appreciation to every author that has participated in this event and to congratulate all of the invited authors who have their manuscript passed the process.

We would also like to give our appreciation to our keynote speakers, Prof. Putra Sumari from Universiti Sains Malaysia, Dr. Kunianingsih, SMIEEE, vice-chair of IEEE Indonesian Section, and my colleague Dr. Eng. Ade Chandra from Faculty of Computer Science and Information Technology, Universitas Sumatera Utara. It is our privilege to have such well-known scientists to share their knowledge at the conference.

Lastly, I would give my highest gratitude to all the international committee, the steering committee, and the organizing committee, who have spent countless times in the last four months. It is an honor to work alongside the current member of the committees that have repeatedly shown an outstanding effort to ensure the quality of the conference.

Thank you

Dr. Elviawaty Muisa Zamzami, ST., MT., MM.

Chair of The 4^th ICCAI 2019

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the proceedings Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

This study aims to create a Safe Parking Application (SPR) using Rapid Application Development (RAD) and Global Positioning System (GPS) which will control and secure motorcycles. Vehicle theft cases increase from year to year in Indonesia's big cities. This application will be a solution to vehicle theft prevention in Indonesia's big cities. It will alert the owner when the motorcycle is moved from its parking position. The owner will receive some detail information about the motorcycle movement i.e. the vehicle location, the history, and the live GPS. In conclusion, the utilization of SPR is a solution to prevent the increase of motorcycle theft in Indonesia's big cities. This application uses a low-cost device as a substitute for an alarm or transmitter.

Forest fire is one of the environmental problems in terms of economically and ecologically detrimental. The number hotspot of forest fires in Indonesia has become increasing dramatically in September 2019 with 16178 hotspots that caused hazardous haze. The hazardous haze has disturbed about 1.04 million and 6.5 million people in Pekanbaru City and Riau Province subsequently. Hence, the development of early warning systems may provide effective strategic information plus accurate prediction results tailored for forest fire prevention and control. Weather data can be used as the main source for analyzing forest fires. This study aims to predict forest fire in Riau, Indonesia. This study has used 1733 weather data in five years (2015-2019). The forest fire prediction models were developed by using two supervised machine-learning techniques namely Decision Tree (DT) and Bayesian Network (BN). The experimental result shows that BN outperforms DT with accuracy rate and RMSE value in pairs of 99.62% and 0.076, and 93.18% and 0.244 subsequently. Despite its low performance, DT able to extract the main factors that caused the forest and land fires efficiently. Thus, it can be concluded that the prediction model using BN has the potential to be used effectively but still has plenty of room for improvement.

Underground object detections usually employ ground penetration radar (GPR). However, GPR produces data taken only from the earth's surface. This paper proposes radio through the earth (TTE) propagation path or received signal profile for three-dimensional detection. The propagation model and the three-dimensional propagation line equation are employed. Collections of transmission paths are classified into two-part, blocked and unblocked signals. Both classified signals are compared for signal processing. The study reveals that a number of the transmission path is a function of vertical edge to probe n, the deep of edge l, and transmitter step s. It is suggested the blocked signal paths are used for signal processing analysis as the volume is usually smaller than the evaluated space.

Load balancing in 802.11 networks is aimed at distributing traffics among access points (APs) to avoid overloaded access. Existing works may be classified into passive and active algorithms depending on the Ethernet changes in the user side. Since Ethernet 802.11 has been installed in millions of computers, changes in these user premises are not preferred. Software intervention on manufactured access points should also be kept as minimum as possible. Therefore, this work proposes a passive load balancing algorithm that transmitting byteless clear to send (CTS) signal in response to a request to send (RTS) sent by unwanted users when AP experiences overloaded. This method causes excessive users will passively be encouraged to find an alternative AP. There is no Ethernet change on the user side. Minor improvement is required in AP software to determine whether overload or not, and to decide which node(s) receiving byteless CTS. Evaluations show that average throughput to all connected users decreases as unwanted users failed to transmit. However, the average throughput to prioritized users increases significantly.

Transmit power reduction is the most common algorithm to achieve load balancing in either 802.11 or cellular networks. The method does not require changes in the user terminal; however, the method requires access point (AP) to have a multi-level front-end power amplifier so that transmission power can be adjusted accordingly. Transmit power reduction also removes the quality of services that may be applied to some users. Such flaws may contradict the value-added services offered by certain access points or cellular base stations. This paper proposes a simple method to avoid power reduction in 802.11 networks. Load balancing is achieved by ordering disconnection for unwanted users by sending a detach clear to send (CTS) signal in response to a request to transmit (CTS) sent by users. Although it violates the standard Ethernet algorithm, it may be applicable in the future standard. By receiving detect CTS, the user is simply disconnected to existing AP and finding the alternative AP. Simulation evaluations show that the method successfully maintains the average throughput as well as maintains the possible prioritized users.

Internet of Things (IoT) has been very assistive in monitoring remote sites by placing some sensors connecting to the internet. Some sensors are located in fully available electrical sources; while some applications rely on the use of a battery. This paper concerns the latest, considering the quality of the sensed data against the power shortage. Vibration detection is chosen as the measured application. The remote sensor was designed by using MPU 6060, controlled by ATmega328 and connected to the internet through an intermediate node using 433 MHz radio. Intermediate node was controlled by ATmega8. Vibration data sent to the internet consists of minor and major vibrations. Major vibration occurs incidentally. Measurement shows that the sorter the data transmission period, the more effective sensor detecting major vibration. It is shown by the increment of vibration amplitude when the transmission period shorter. However, the more frequent the transmission, the more energy required. The assessment shows that data quality and power lifetime are determined by the transmission period.

The guidance of Muslims in worship refers to the holy Quran and the hadith. Not all people understand the law related to a case in accordance with Islamic teachings. Questions relating to a matter based on Islamic law are widely circulated on the Internet with long and detailed answers. This is good but for some people, a short and direct answer to the core is the desired answer, of course in accordance with the majority of Muslim scholars. One of the many technologies that can be used to answer questions is chatbot. A chatbot is one of many implementations of Natural Language Preprocessing. In this study, the chatbot can find answers to questions in accordance with Islamic law using the fuzzy string-matching algorithm. The research test data were obtained from several people who used chatbot directly by looking at pairs of questions and answers whether they were appropriate or not. The accuracy of the test is 70.37% and the chatbot's performance is quite good.

Traffic accidents are the most feared thing for everyone. Even though people are careful using vehicles, accidents can occur. This can be caused by humans not obeying traffic rules, drowsiness, damaged roads, and bad weather. In recent years the accident rate in Palangka Raya has increased sharply and even resulted in death. Accidents often occur in different places and times, making it difficult to determine accident-prone areas. By utilizing data mining techniques using the K-Means method, it can explore information on areas where accidents occur frequently. So that it helps the police in providing signs of accident-prone areas. The results of the study stated the K-Means Clustering algorithm in determining the accident-prone point of success obtained by 68%.

The real research strength of an institution is important for establishing research priorities and developing an institutional research plan. It can also be used as a basis for SWOT analysis, developing vision-mission of an institution and also useful for research funder in distributing their research grants. Unfortunately, there was only a small number of researches found. In this article, we proposed a new method to quantify the quality of research outputs. The method is suitable for measuring research strength. We applied the method to an institution using research articles downloaded from a reputable document database/index. The results were research strength map in 27 subject areas and 337 subject categories.

The purpose of this paper aimed to investigate the impetus and influences of executing Online Learning Interaction in the Global Class Program. There were sixteen university lecturers involved in this study. Data were collected through an online survey using Google form. The analysis of data used descriptive analysis using percentages. The results indicate that Online Learning Interaction carried out in English classrooms resulted in positive effects for university lecturers. The most influential effect of executing Online Learning Interaction to facilitate lessons in English was aiding to enhance technological skills in learning. Then, the second biggest effect was facilitating to transformation global vision or mindset of the lecturers. The third and fourth places were improving the effectiveness of communication in learning and enhance delivering skills. Moreover, the study indicates that ICT satisfaction in learning was the dominant motive to execute Online Learning Interaction in English Classroom contexts.

One crucial step in detecting intra-cerebral hemorrhage automatically is to develop a midline setting that will divide the brain structure into 2 parts: the right hemisphere and the left hemisphere. This is useful for the process of detecting bleeding in the brain. By comparing the right hemisphere and the left hemisphere, bleeding detection can be done quickly and automatically on the application system. In this study, we proposed a method that was developed based on the pixel scan algorithm and the determination of the center of weight of the segmented part of the brain. The midline was set as the longest line possible drawn from edges of the brain skull. The result was then compared to manual reading by conducting user agreement surveys to radiology experts. The result shows that more than 75% of the cases experts strongly agree and agree with the midline setting automatically set by the algorithm, but 65% of them were dissatisfied and suggested improvement of the algorithm.

Face recognition is a topic most often discussed in this era because it can be applied and developed for several needs that can be useful in daily life. Face recognition always use learning method like eigenface and learning vector quantization (LVQ). The learning process is using the face of a digital image taken from a camera in five angles for one person that will apply for dataset learning (training and learning data set), and the live image is taken from the camera for testing (testing data image). The first step image will be detected with a haar cascade and captured by a camera. It will use to processing images to get the best image and prepare to be input into the network. From the experiments with 10 testings with various parameter values, the experiment results obtained the LVQ is more accurate than eigenface to identifying faces with average accuracy 66.29% and eigenface is 56.67% with comparison 9.62%, but eigenface is faster in running time with average time 4.39 seconds and 7.38 seconds for LVQ with comparison 2.98 seconds.

This paper described the design and numerical simulation of a rectangular microstrip patch antenna for applications at 3.35 GHz. The numerical simulation carried out with the aid of AWR software. The initial design was done by mathematical calculation. Then the initial design is modeled and numerically simulated to get the optimal design. Optimized parameters are length of the patch and width of the feed line. Based on the optimal results obtained a minimum return loss of -15.98 dB and bandwidth below the return loss of -10 dB is 93 MHz (3.311 - 3.404 GHz).

In big and metropolitan city, traffic jam is common problem and often to be occured. And that is the most critical problem for emergency vehicles. Where time and urgency are the most priority to be handled. In this research, emergency vehicle was utilized with any GPS device. The vehicle tracking service is provided for real time tracking. We use open source vehicle tracking framework/server Traccar. The same as with common GPS device, the emergency vehicle continusously sends its latitude, longitude and speed to GPS server. The research focused on Traffic Light Device which built of ESP32 microcontroller, GPRS module Air202 and battery power supply with charging function. While emergency vehicle reports its position to GPS server, the traffic light device continuously checks the emergency vehicle's position data from the GPS server. The idea is to take the advantage of GPS server API, where traffic light device using HTTP GET communication with implementation of embedded cookies, session and keep alive to access the GPS server API. Traffic light device then calculates straight distance to emergency vehicle based on its predefined fixed latitude and longitude. If emergency vehicle located within the user defined threshold radius of traffic light device, then the traffic light turn green to allow emergency vehicle for passed its line. As the result of this research, traffic light device has been successfully read emergency vehicle device's location data and measured their distance within 1 to 2 seconds.

The use of technology makes information spread more quickly compared to conventional methods that humans used before they knew technology. However, there is information that is only intended for certain people or institutions because the information is very confidential. The obstacle in exchanging information is the problem of information / data security. Because of that, an electronic message security algorithm which is quite well-developed is cryptographic (cryptography) and steganographic (steganography) algorithms. The development of increasingly advanced technology and the addition of more and more computer users also cause data to accumulate and transfer data from one device to another. The data is generally compressed first so that the exchange process does no take too long. Therefore, we need a system that can secure messages while reducing image data to be more efficient in the process of transmission and delivery. To implement this problem the system is designed using the Linear Congruential Generator (LCG) algorithm and the Most Significant Bit (MSB) as a security medium and using the Fibonacci Code algorithm as compression of the image. In implementation the system has a weakness in compressing images that not dominate colors because the size of the data becomes larger. In addition, the compression ratio on the variation of text length has decreased and has increased in the image variation experiments where if the compression ratio decreases, indicating better compression.

Accurate and timely identification of plant disease can help stakeholders and farmers to mitigate losses due to pests and diseases. One of the identification techniques is indirect detection using thermal imaging technology. This technology has been considered a fast way without damaging the profile of a plant. In this paper, we describe the preliminary study of the thermal images gathering, so that the rice plant disease on the leaf canopy can be identified by using a thermal imaging camera.

Air pollution is one of the environmental problems faced by many countries (i.n. the developing countries). It often harms the health of people, plants, and animals as well as our environment. To decrease the risks, e ective and e cient technology for air quality monitoring is indispensable. In Indonesia, it is still limited in the case of the number of devices and the dissemination of air quality information. This paper describes the preliminary research design of air quality monitoring technology based on the Internet of Things (IoT) and Natural Language Generation (NLG) for solving these limitations. It de nes air quality knowledge in the form of a set of rules and presents the architecture design for data gathering and text generation. Data gathering uses the related sensors which are able to collect the values of parameters as air quality indicators. Then, the collected values are identi ed to be used for generating the textual information in Indonesian language to social media, such as twitter. So, in this research, the proposed solutions are able to solve the problems properly.

Scale model is a necessary building design in architecture as a way for architects to represent the results of the design as a physical model. The making of scale model requires components that costs some money. With the development of Augmented Reality (AR) technology, designer could bring the model design without having to make a scale model through marker tracking on a brochure. However, with the development of the technology itself, the researcher applies an AR method that can put an object in real environment by detecting flat surfaces. The method is Markerless AR. With this method, the use of marker tracking which requires a marker to remain on the frame of the camera is no longer needed. The technique in the new method will use plane detection that can detect flat surfaces by specifying points on the textures of the frame which is captured by the camera. The necessary stage is to define point cloud that will be used to mark the textures and the plane as a place to put the model in the form of virtual object. Object placed above the plane will remain stable despite having the camera moves around it, the plane will not move around because it is a result of virtual projections. The result of using plane detection will provide a space for the user to observe the model more clearly, such as on a floor or on a table because the model can be rescaled and rotated. Users also can move freely without being hindered by the marker tracking.

Dengue fever is the most hurriedly diffused mosquito-borne viral disease in the world. More than 33% of the total population in the world is under risk. Currently the prediction of dengue can save a person 's life by alerting them to take proper diagnosis and care. The Objectives of this research is (1) To Predict The area with the most potential to suspend dengue fever In Indonesia, And (2) to Predict dengue fever cases. (3). To analyz how many percent the effect factor of dengue fever. There are many ways to predict one of them is Regression and Deep learning Approach. Reseacher tried to analyz the most accurate such as Regression Multyplied, Neural Network, and Sensitivity Analysis. Set of data have been used is timeseries from 1997—2017. The Variable has been used for this research is Humadity, Temperature, Wind, Airpressure, Rainfall Index, income, sunlight, Population density, and output is cases. The Result of this research is first The area with the most potential to suspend Dengue fever In Indonesia 2019 is Jambi, Lampung, Bangka Belitung, West Sumatera, Central java with average Accuracy 87,16%. The Prediction dengue fever cases 2019 is 80233 Cases with accuracy 87,16%. The Third All variable ( X1 s.d X8) have been to effect to Partial and Simultaneous to (Y) in the amount of 0.16 (16 % ) with a significance level of 0.001 (99%). While the remaining 100% - 16% = 84% is influenced by other variables outside of this research.

Software development usually follows the stages known as the Software Development Life Cycle (SDLC). Development begins with the requirements phase and then continues with the design, development of test plans, implementation (coding), testing, and deployment. However, the security aspect has not been explicitly reflected in SDLC. In fact security must be present at every stage of the SDLC. Application of security in the process of developing software, especially e-Commerce, one of which uses the Security Development Lifecycle-Agile (SDL-Agile) method. The advantage of the SDL-Agile method is the application development process which incorporates a safety factor in each application development process, which is concise, and emphasizes user satisfaction. This objective of this paper examine the deployment of SDL Agile Method for eCommerce website to measure its confidentiality, integrity, and availability of the systems.

The placement of elementary school teachers is an NP-complex problem. Teacher placement can be optimized by considering several factors that influence their performance, including the distance of teacher's residence to school, age, and gender of the teacher. This paper discusses the solution model of the problem based on genetic algorithms by finding a chromosome formation that represents the possibility of teachers placement solution, composing a population, and finding the recommended combination of two selected mutations operators and two selected crossover operators to achieve optimal results. The selected mutation operators were Reverse Sequence Mutation (RSM) and Partial Shuffle Mutation (PSM), while the selected crossover-operators were Single Point Crossover (SPX) and Ordered Crossover (OX). The combined performance of these operators is measured based on the fitness value and running time of the program. Based on experiments, it can be concluded that the combination of OX-PSM with mutation probability 1:20 gives the lowest minimum fitness value compared to other combinations of crossover and mutation operators. The running time of the combination of OX-PSM is stable in any mutation probability, ranging from 39,5 – 41 minutes.

The problem of this is still very interested domestic and foreign investors to invest in remote areas of Indonesia (3T) Disadvantaged, Outermost, Frontline whereas 3T Region has a very promising potential from various sectors. The purpose of this paper is to see what is best and best for investments that will provide positive results for both foreign and domestic investors. The analytical process used is the neural network and sensitivity analysis used to predict and determine what is most likely to be done investment. The results of the analysis in this paper are from the sector which analysed that is the sector of Hotel and Tourism Industry, Trade and Retail Sector, The most profitable E-commerce, Infrastructure and Construction, Plant and Agriculture business in 3T area is 1. Infrastructure & Construction, with value output 0.8269 2. Factory & Agriculture with output 0.7995 3. Hotels and Industries with output 0.7688 4 Retail trade & sector with output 0.82695. Ecommerce and Business with output 0.0261 Furthermore from 5 Regions which are sampling 3T area that is Aceh Singkil, Nias, South Nias, Coastal west Lampung, Mentawai Islands, Potential area for investment is 1. Five.8219 2. Mentawai with output 0.8021 3.West Lombok with output 0.7719 4.Nias with output 0.7072 and 5.South Nias with output 0.0272.

Schools, colleges and universities are now embracing the use of visual aid presentation (e.g., PowerPoint) in the classroom. Studies have consistently indicated that students generally believed that the use of technology for oral presentation would facilitate their learning. Students in such condition believed that the class was more organized, clear and interesting. Students also liked the teacher/lecturer more and indicated that they would like to take another class from the teacher/lecturer when the he or she used technology means of presentation. This research was focusing on the perspective of students in Binus University regarding the advantages or disadvantages of this model of learning process in regard of interesting or boring and long or short endurance of understanding. The visual aid presentation here meant that the students were the ones who were performing the presentation, instead of the teacher/lecturer. The research method used was descriptive qualitative based on the survey and interview of some sample students who were chosen randomly, who were taking English course in first/second semester.Based on some researches, the visual aid presentation in learning process was showing positive impact for teachers and students. Therefore, the hypothesis on this research was that the visual aid presentation on learning process would bring an interesting environment, long endurance of understanding and improving students' behavior. It was expected that the result of this research could be used to improve the learning method of English learning in Binus University in order to support Binus Vision to be a global university and to enrich graduates with the skill of oral presentation.The respondents were selected from management students in Binus, Alam Sutera Campus, and randomly chosen. All of the respondents replied that learning by doing presentations was giving more understanding on topics, boosting up self-confident, teaching public speaking, handling nervous and creating a dynamic class environment to avoid boredom. From the students' point of view, this learning method was giving advantage for students and long endurance of understanding.

We present a simulation of proton exchange membrane fuel cell (PEMFC) system to convert the chemical energy stored in hydrogen into electrical power. The PEMFC model was developed using Aspen Plus and then analyzed to find the electricity generated. In the PEMFC system simulated in this study, hydrogen gas enters the heat exchanger prior to entering the anode to increase its temperature up to 80 °C. Around 80% of hydrogen used during electrochemical reactions with the oxygen, which entered from the cathode side. The proton and electron of the hydrogen combine, react with the oxygen provided, and produce water and heat. Based on the analysis, the power generated by the PEMFC system is 0.23 kW with current density of 1 x 10⁻³ A/m² and MEA area of 3 x 10⁻² m², and the number of cells in stack is 135 cells.

The government has now taken a policy to replace the use of fossil fuel oil, such as gasoline and petroleum diesel, into gas fuel. A converter kit and the modification of air filter are used to flow LPG (Liquid Petroleum Gas) into a generator. In this experiment, a three kg gas cylinder is used as fuel to run a gasoline generator engine of EG 1000 N S Type which is produced by Honda. The engine has a specification to generated power of 220 volts with 4.1 A outputs and 0.9kVA (720 watts) when operated using Gasoline fuel. The electricity produced during the operation of the generator engine is 680-700 watt when fueled with LPG. It was found that the generator engine fueled with LPG contributes to lower emissions which are still following Indonesian government regulation standards with a threshold value of CO and nitrogen oxide less than 500 mg/NM³ and 400/NM³, respectively.

Nowadays, transportation plays a big part in our daily lives. Everyday, people in Indonesia are increasingly using vehicles especially motorcycles. Unfortunately, along with the increasing number of motorcycle users, motorcycle theft has also increased. In this paper, we propose the prevention of theft and recovery of motorcycles by using sensors and microcontrollers connected to smartphones. In case of theft, the sensor will be activated automatically and the user will be notified by this system via an alarm warning. Users not only can see the location of the motorcycle at this time but also can turn off the engine through a smartphone even though the distance is long as there is an internet network. The results showed that the system can turn on/off motorcycle engines automatically using an Android Smartphone. The vibration sensor could activate the alarm and send a notification to the owner of a motorcycle. The motorcycle can be monitored by GPS devices that have been embedded on a motorcycle.

Nowadays heart attack is becoming a very deadly disease of human. This attack cannot be predicted, but it can be known from the human heartbeat which is a very vital health parameter of the human cardiovascular system. Heart rate reflects the health conditions of the human cardiovascular system that determined by such as stress at work, before or after sports and the psychology factor. Unfortunately, some people do not know their heart rate before or after doing an activity. This paper proposes of measuring technique of heart rate by using pulse sensor, Arduino microcontroller, and Android Smartphone. It is based on the principle of measuring the variation of blood volume in our body using a light source and detector. We also measure the heart rate by using the ECG or EKG (electrocardiogram) waveform as the comparison result of the pulse sensor with ECG waveform. The sensor consists of an infrared light-emitting-diode (LED) and a photodiode. The LED transmits an infrared light into the fingertip which is reflected back from the blood inside of finger arteries. The results show that this tool can detect the value of the heart rate and is displayed on the screen of an Android. The sensor takes under 10 seconds to detect the value of the heart rate. Notification via SMS will be sent the heart rate such as under normal conditions (BPM, Beat Per Minute <50, normal (BPM = 60 to 100) or above normal (BPM> 100).

Hamming distance between two vertices of a finite simple graph is defined to be the Hamming distance of rows of (0,1)-matrix of the graph correspond to the two vertices. Hamming index of a graph is the sum of Hamming distances between all pairs of vertices in the graph. In this paper, we introduce the notion of additively weighted Hamming index of graph where the Hamming distance between two vertices is weighted by the sum of the degrees of the two vertices. We discuss the additively weighted Hamming index of a graph with respect to adjacency and incidence matrix of the graph. We relate the additively weighted Hamming index of a graph to the order of the graph, the size of the graph and the degree of each vertex in the graph. We then use this relationship to determine the additively weighted Hamming index of graph whose vertices have almost uniform degree.

Social network extraction from information sources, as a research, requires the right steps. However, it is not enough, it need accurate description that explains the steps in one framework so that the flow of the extraction implementation information is well, as well as the extraction occurs systematically. In this paper, a framework for social network extraction has been outlined by involving several formulations and measurements as an explanation.

This paper provides a classical interpretation of mathematics from terms to categories such as arithmetic, geometry, algebra, and trigonometry. The background of interpretation is based on mathematics itself as reasoning, which contains systematic and structure. However, the mathematical term is recognized by them, but it comes with a variety of symbols and ways of interpretation. That interpretation is accumulated into universe of discourse which is a means of mathematics itself, and it states the mathematic.

Naturally, human do the search for truth in various ways. All of that becomes methodological, but not a methodology. The right way and produce truth by involving the principle of believing the truth, getting a way, and having a purpose. So, its not justification. Three basic principles of methodology are not enough. However, the methodology becomes the method science, it needs to be systematic that flows the truth logically, and needs a structure to form the truth logically. Thus, abstraction is helped by rules or formulations that describe the structure, at least from the point formation, as definitions, lemmas, propositions, theorems, or corollaries.

The Batch Training method is one of the methods of Artificial Neural Networks that can be used to make predictions, especially in times series data. This method is able to make predictions by learning from data that has never happened before by forming the right network architecture model. Therefore, this research will discuss the best network architecture model that is appropriate for making predictions using the Batch Training method. The data used in this study is the data of Natural Disasters in Indonesia, sourced from the National Disaster Management Agency. There are 12 variables used, namely Time of disaster, Number of disasters, Death and missing victims, injured victims, victims suffering and displaced, seriously damaged houses, lightly damaged homes, submerged houses, damage to health facilities, damage to worship facilities, and damage to facilities education. Based on this data will be formed and determined the network architecture model used, including 4-5-1, 4-10-1 and 4-15-1. From these 3 models after training and testing, the best architectural model is obtained 4-10-1 with an accuracy level of 91% with MSE Training and testing values of 0.0245532940 and 0.0579265906.

Indonesia is one country that is known for its natural wealth. Various types of flora and fauna living in this country. Examples of rich fauna that exist in Indonesia and can still be found at this point that one-horned rhino (Java rhinoceros), Sumatran elephant, Sumatran tiger, deer Bawean even dragons. However, over the times that make more and more people are not responsible for expanding residential land for private purposes and poaching that occurred in Indonesia, the animals are increasingly difficult to find because of habitats and their populations are dwindling. In this research, researchers applied a mixed reality technology with voice input to bring the Indonesian endangered species that has begun difficult to be found with the actual scale without having to disturb the habitat or environment. How it works is a mixed reality which brings together the virtual world with the real world. So that thanks to the development of today's technological world, users can feel the direct presence of these animals without having to hunt or look for them.

The presence of new science does not necessarily occur just like that. Every science starts from interests, discussion, and looks for a basic foundation, but in general the main foundation of science is mathematics. Data science includes structured and systematic knowledge about data. However, many other sciences that has a relationship with the data in question, ranging from statistics to computer science. This paper aims to reveal the obstacle and limitations of other science into a data science completely, on that basis the definition of data sciences needs to be elaborated, then confirm data science as new science and not depend directly on several other sciences.

Single Nucleotide Polymorphism (SNP) is a type of molecular marker which constitutes the phenotypic variations between individuals in certain species. In recent years, the advantages of SNP were widely considered in many fields, for instance in designing precision medicine in humans and assembling superior cultivars in plant breeding. The main challenge in SNP discovery is imbalanced data distribution between classes, where the number of true SNPs in question is much fewer than false SNPs. While the study in observing the benefit of feature selection in classification problem was widely reported, the use of this technique in solving imbalanced class problem still become interesting topic for research. In this study, we selected the features that most contribute in identifying SNP using Feature Assessment by Sliding Thresholds (FAST) method. FAST evaluates the contribution of each feature in identifying SNPs based on the Area under ROC Curve (AUC) value. SNP identification using 4 best features resulted in improved classifier performance in terms of G-Means compared to using 24 features. In addition, using feature selection techniques can reduce computational time and save resource needed.

Landslide early detection system consists of a sensing system and an alarm system that is not in the same location (remote area). The sensing system is located in a vulnerable area, while the alarm system is placed in a residential area. The sensing system uses sensors found in Plug and Sense from Libelium to read rainfall, soil moisture and soil movement and use a 3G module. The alarm system uses Arduino Uno R3 as a controller and has a Relay and SIM800l module. The installation area of the system depends on the area that has an internet network. From the overall test results, the system successfully measured rainfall, soil moisture, and soil movement. The system also managed to activate an alarm if there is a potential for landslides and successfully sends measurement data to the website. The activation of the alarm system has a delay of about ± 30 seconds. Keywords: Landslide Early Warning, Plug and Sense Smart, 3G, Arduino, Waspmote.

Artificial Neural Networks are often used in the fields of pattern recognition, speech, and image recognition, where high levels of computation are needed. One method that can be used is the Back-propagation Neural Network. The method can be used to identify several diseases, one of which is a cataract. A cataract is one of the most significant diseases that can cause blindness. Cataracts consist of three levels, namely mature cataracts, immature cataracts, and hyper-mature cataracts. The testing method uses two parameter values, namely epoch with value 1000,5000,10000 and learning rate with value 0.01, 0.05, 0.1. From the test, it was found that the best parameters of the above trial results were epoch with a value of 10000 and learning rate with a value of 0.1 on 80 experimental data. In experiments conducted to identify normal, mature, immature, and hyper mature obtained an accuracy of 100%, 95%, 85%, and 90%. The percentage value of the accuracy of the test results using the BPN method is 92.5%.

Sudoku is a pretty popular number game. The goal of this game is to fill a 9x9 matrix with unique numbers, and there should not be repeated numbers in each row, column, or block. This paper proposed a solution to solve Sudoku using the Backtracking Algorithm. This algorithm is quite efficient because it does not have to check all the possibilities that exist, but which leads to only the solution that will be processed, namely by pruning every element that does not lead to the solution. Thus the time required is quite efficient and suitable for use in reasonably complex numbers games like sudoku. By implementing the backtracking algorithm in the sudoku game, the complexity of the algorithm can be as large θ (n³).

Indonesia's strategic position between two continents and two oceans has resulted in an obligation for Indonesia to be involved in various international cooperation and international conflicts. The declaration of the development of the maritime sector to be the cornerstone of Indonesia's main strength requires support from the air defense sector. The current condition of Indonesia's air defense sector, especially the Air Surveillance Radar has not worked optimally resulting in an air defense operation that has not been maximized. The properties of high-frequency electromagnetic waves used in Doppler radar have a straight line of sight. Mountains, hills, and artificial objects/buildings can become obstacles, create blank areas (areas that cannot be covered by radar) behind them, and reduce the performance of the radar coverage. The use of sensing technology, in particular, the geographic information system to determine the position of air surveillance radar placing is an effective solution to optimize the coverage radars exist. The rectangular rule approach method combined with the land surveying technique is a combination of methods that can be used to measure the volume of air defense radar coverage. The level optimization of radar position planning point can be determined by processing the obstacle volume, land slope, earthquake and landslide vulnerability, and land cover conditions into the calculation of the fuzzy inference system technique. This study examines the concept of using Geographic Information Systems to measure the level of radar optimization when placed in a planned position. This research aims to produce a method review on optimizing the performance of air surveillance radar coverage by utilizing remote sensing technology to determine the radar placement position.

As computers with manycore architecture are being widely spread, parallel programming becomes a pending issue. While parallel programming has been a challenging issue, Haskell is known to be of the best available one. The immutability and declarative nature of Haskell suit well the need for parallelism. In our previous work, we implemented the SAM, a parallel programming model based on Haskell. In this paper, we propose the SSAM, an updated version of SAM, by solving the performance overhead of SAM socket. We discuss the architecture of SSAM and its major functions and show the 14% scalability upgrade in a performance test.

According to the e-Marketer market research institute, the net population of the country reached 83.7 million people in 2014. With this amount, Indonesia has been included in the 20 most internet user countries in the world. MOBA is currently in great demand. The high level of competition of this type of MOBA game attracts a lot of game players' attention to tournaments or competitions officially both regionally and internationally. In 2013 there were around 71.5 million e-Sports enthusiasts around the world. Every year the number of Indonesian gamers is estimated to increase by around 33 percent. With a growth of 33 percent, this certainly makes a great opportunity for game developers. Currently, the games circulating in Indonesia is mostly from foreign countries such as America, Japan, and South Korea. Each hero has a different role (ability). The foresight of players and the ability of individual skills are determined by selecting the composition of hero roles on a team to achieve victory in the legendary mobile gameplay. Naive Bayes Classifier is the simple Statistical Bayesian Classifier. Naive Bayes is able to classify role heroes well enough to predict the victory based on the role hero chosen by the player. Naïve Bayes implementation can explore the characteristics of the attribute and dataset of the chosen role hero. Naïve Bayes algorithm method can predict the Victory in mobile legend gameplay from existing hero roles based on datasets and training data.

Power generation using Organic Rankine Cycle (ORC) was studied in this paper. A thermodynamic model was achieved in Aspen Plus environment and the highest output power and efficiency were obtained for on variance working fluids. The Organic Rankine Cycle (ORC) is analysed using commonly used working fluids for cycle use, they are R245fa (1,1,1,3,3-Pentafluoropropane), R11 (Trichlorofluoromethane), and R123 (2,2-Dichloro-1,1,1-trifluoroethane) . The results show that some of the effects of the pressure on the inlet turbine, and working fluids variances on the performance of the cycle. The output power turbine and efficiency of the system were simulated and discussed.

Stock market prediction has always been a difficult process, most of the prediction rely solely on the data of the corresponding stock market. Relationship of gold and oil price with stock market performance has been proven significant in some major world stock index. Prediction of stock market price index using machine learning methods is expected to perform well, with the ability of machine learning method to predict using nonlinear inputs. The methods were commonly able to predict relatively well in predicting the values of Japanese Nikkei 225 and Japanese Nikkei 400 indexes.

The learning process undertaken by each school is face-to-face between educators and students; of course, this method will lose its appeal to meet digital education 4.0. So that education personnel and students should be able to adjust the p Indonesia Economic technology and information that constitute a significant role as a medium for help, search, analyze, and obtain information about learning. The learning process to welcome digital education 4.0 cannot be separated from various computer devices, the internet, which can be done online (e-learning). To get good learning outcomes, of course, technological development (e-learning) must be able to benefit right, without having to leave face-to-face learning (face-to-face). For this reason, there are teaching models/strategies, teaching delivery, and the right quality of teaching, one of which is the Blended Learning Model. Blended learning is a learning model that combines the advantages of face-to-face learning models with e-learning learning models. With blended learning interaction and communication between educators and students can take place because this model is one of the active learning methods to deal with digital education 4.0.

At this time the development of technology that forces everything must move fast, the efficiency of time becomes a measure of the success of a distribution or production. the continuity of production and the success of production itself is related to distribution. When the distribution fails, production will fail. Indonesian people especially in North Sumatra often consume snacks when free time and snacks are the most consumed food by the Indonesian population until now the production of snacks in Indonesia rose to 50% in 2019, causing the food production to have a concept in timely distribution without experiencing delays in distributing goods that have been produced. One of the expeditions in Indonesia experienced problems in terms of late distribution of goods up to 15-20%, this would have a bad impact on the industry in the future, so to overcome the problems above the application of the ant colony optimization algorithm can help the above problems by placing 4 ants and the ants will spread from point A to point H. In the results of this study, there are 4 ants that move together where the best results are obtained by ant 2, closest to the point H, where the value obtained reaches 0,00015

This article discusses the implementation of the k-NN algorithm in predicting student behavior. The school is a management unit that has data that correlate with students. All student data is stored in an academic information system that can be processed to predict student behavior. One of the data assessing student behavior is in the database of counseling guidance. Some data that will be processed include attendance, lateness notes of problems, teacher responses, tuition payments, broken home. The sample being tested was the data of 100 vocational students from various classes and various majors and divided into two categories. From this experiment, it can be seen that the most accurate K value is the value of K = 1, 3 and 4. The accuracy of the testing data generated is 94.9%.

The research objective is to recommend the sale of the best ornamental plant species to lovers of ornamental plants by using decision support system techniques. Ornamental plants are a type of ornamental plants that can survive in various conditions. In this case ornamental plants are also very vulnerable to disease such as root rot, shoot rot and others. Many types of ornamental plant sellers do not know how to handle ornamental plants that have diseases or symptoms when they occur. The study was conducted in Simalungun District with a sample of thirteen traders selling ornamental plants using observation and questionnaire distribution techniques. Selection of ornamental plants based on the types in this study include: Orchid Plants (A1), Tulips (A2), Bougenvil (A3) and Jasmine (A4). The assessment criteria used include: Plant height (C1), Plant quality (C2), Plant type (C3) and Plant age (C4). The method used in this research is Simple Additive Weighting. The results showed that Orchid Plant (A1) was the best alternative for selling ornamental plant species (V1: 0.91) and Jasmine (A4) as a second alternative (V2: 0.8).

This study investigates the legality of practitioners in interpreting UU PP (Electoral Act) to provide guidance in technical and managerial aspects especially in relation with principle of privacy by applying content analysis with percent agreement and Cohen Kappa. Thus, this study design code paper to be distributed to 21 coders to gain more understanding the approach which is appropriate to synergize various interest in election to bring more appropriate management to align with voters expectation especially in regard to privacy policy. The highest disagreement among coders occurred between coder 8 and 20 with -0.285 of Cohen Kappa and 0 of percent agreement while the highest agreement between coder 2 and 7 with 0.727 of Cohen Kappa and 93.2 of percent agreement.

A wide range of new opportunities for fraudulent online activities has arisen with the growing popularity of online shopping and big data issue. E-payment fraud schemes are collecting billions of dollars from customers, distributors and service providers every year. A lot of machine learning methods for fraud detection problems have been proposed which can be categorized into supervised, unsupervised and semi-supervised methods. In this paper, we proposed biologically inspired technic in the feature engineering phase for handling imbalanced data to increase the total data of a small number of classes by oversampling. One-point crossover used to generate the new data of minority classes. The best algorithm performance obtained to predict the fraud transaction from various machine learning models is Classification and Regression Tree with the corresponding accuracy, precision, recall, and F-1 Score are 96%.

Digitalization and internet penetration force telecommunication companies to perform a transformation to survive, to face competitions, and to gain opportunities. PT XYZ is a telecommunication company that has introduced a new leaner and agile working method for digital transformation. The organization is undergoing a transformation to implements an agile approach using a scrum framework. There are two divisions that use scrum that currently plagued with time estimation difficulties and inability to create an agile backlog due to the old change request mechanism. Scrum Maturity Assessment (SMM) is used to measure current scrum practice maturity. The data is retrieved using a questionnaire that was given to two Scrum Master from two divisions which have been implementing Scrum. There are 83 questions derived from SMM assessment questions. SMM assessment indicated the scrum practice is Level 1 (Initial). There are 31.76% of scrum practices in IT division and 36.25% of scrum practices in CS division need to be improved to achieve Level 5 Optimizing. In order to achieve Level 5, we proposed 38 steps and six recommendations which will guide the scrum practice improvement process.

This paper investigates how the instruments of E-Learning Usability Scale adapted in the Indonesian context. The need for adapting the original version arises while assessing the usability of e-learning in a higher degree in Indonesia, namely Student-Centered e-Learning Environment or (SCELE). In the process of usability evaluation, a questionnaire is needed. E-learning Usability Scale (EUS), which is created by Sandoval (2016) will be used as the usability scale. However, the EUS was originally built in the English version and it has not been developed in the Indonesian version. Overall, there are five steps to adapt the usability scale to Indonesian culture which are forward translation, synthesis of the translation from the first step, back translation, consulting to the experts, and reliability testing. The results show that Croncbach's Alpha of the adaptation Indonesian of EUS was 0.922. It can be concluded that the proposed version is reliable to be used by usability researchers. In the future, the adapted version that is proposed in this study is beneficial to help usability researchers, academicians and practitioners in Indonesia while conducting usability testing for e-Learning applications.

As a country with the largest number of medicinal plants in the world, Indonesian uses medicinal plants as a composition of herbal medicine. The ingredient of herbal medicine is generally made based on experiences and hereditary. This research aims to build a scientific background of Jamu through analysis of the relationship between medicinal plants used as the composition of Jamu and its therapeutic usage. Deep Learning was chosen as a classifier because it shows good effectiveness in generating predictive models in many studies. As a comparison, we also applied the Random Forest and Support Vector Machine as classifiers and examined the classifier performances while predicting the therapeutic usage of Jamu. To handle the imbalanced data between efficacy classes, the Synthetic Minority Oversampling Technique was applied before model generation. The result shows that the highest accuracy for Deep Learning is 88.74%, relatively higher than Random Forest and Support Vector Machine, which obtain accuracy values of 78.84% and 77.60%, respectively. Variable importance of the best prediction model using Deep Learning identified 105 medicinal plants, and 39 of them were selected as potential plants for 14 therapeutic usages.

Since the first appearance of the Massive Open Online Course (MOOC), the problem of low completion rates in MOOC has often been an object of research in terms of the instructional design and interface design. However, in-depth studies that examine the implementation of instructional and interface design principles in learning on the MOOC platform are still limited. Therefore, the purpose of this study is to find out the extent of Udacity in applying those principles from the Indonesian perspective. This study also aims to evaluate the usability of the MOOC platform. There are 228 participants in this study from various regions in Indonesia. The study findings indicate that Udacity has been successful in implementing content, interactivity, and course design, but there is still room for improvement in terms of instructor presence. Some usability problems were also found, and most of them are related to the online discussion forum. This study also offers an alternative design and recommendations to tackle the problems.

Dengue Hemorrhagic Fever (DHF) is one of the common and fatal diseases in Indonesia. Jambi city is one of the dengue-endemic areas in Jambi province. To reduce the incidence rate of dengue, an early warning based on forecasting is necessary. Time-series forecasting of DHF can provide useful information to support and help public health officers for planning on DHF prevention. This paper compares two methods for Time-series forecasting of DHF incidence, namely seasonal autoregressive integrated moving average (SARIMA) and Long Short-Term Memory (LSTM). The forecasting performance is assessed using the monthly number of DHF incidence data from January 2012 to April 2019 were acquired from the district health offices. To show the effectiveness of the model, the performances are evaluated based on two metrics: mean absolute error (MAE) and root mean square error (RMSE). In the first analysis, we found that the SARIMA ((1,0,0) (1,0,0)₁₂) is the most suitable model to predict the number of monthly DHF incidence with RMSE value of 30.07 and MAE 18.97, and the second one used the LSTM with one hidden layer (1-64-1) architecture with RMSE of 30.41 and MAE 18.27. Based on the experiment between SARIMA and LSTM perform relatively well to predict the future.

The lecturer and employee attendance system that is widely used today is the system using a fingerprint device that is placed in every department or faculty. This system has shortcomings such as the limited availability of fingerprint scanners, the presence of presence equipment that is far from the work location, and dependence on the presence tool. So with this weakness, the presence application system is based on mobile apps that use GPS and fingerprints to facilitate lecturers and staff in making a presence while in the presence area or where they work. With this system, this will make the presence and processing of presence data more accessible and more efficient, so that it can help maximize the process of gathering and processing the presence data. From the system testing, the system can process employee data, display the results of the daily attendance, and can store the results of the presence and obtained system sensitivity of 65%, specificity of 70% and system accuracy of 72%.

The amount of time spent in requesting and waiting for the meal in Martabak Air Mancur restaurant may permanently multiply the number of customers in the line waiting especially during peak hours and on weekend. It will affect the quality service of the restaurant and the loyalty of the customer. From the observation, most of the customers spent a great deal of time making an order when faced with many proportionate choices. The study proposed a system by using self-service technology and the waterfall model. In the beginning, the time needed from making an order to finishing the payment is 15 minutes. The system built can reduce the transaction time to 10 minutes.

The recommendation system is one method to know the preference consumer by showing the potential object. This recommendation also helps the consumer gets the preference object. One of the popular objects in the recommendation is anime film. In this case, we conduct research to recommend anime films based on ratings of previously watched films. Collaborative filtering is a technique that consists of calculating similarities, predictions, and recommendations. This study is taken from dataset Kaggle which consists of 73,516 users and 12,294 anime. A user's history will be matched with the whole user's history with alternating least squares (ALS) method. The anime will be recommended based on that results. This method is expected to help millions of users find the desired anime.

K-Means is a clustering algorithm based on a partition where the data only entered into one K cluster, the algorithm determines the number group in the beginning and defines the K centroid. The initial determination of the cluster center is very influential on the results of the clustering process in determining the quality of grouping. Better clustering results are often obtained after several attempts. The manhattan distance matrix method has better performance than the euclidean distance method. The author making the result of conducted testing with variations in the number of centroids (K) with a value of 2,3,4,5,6,7,8,9 and the authors having conclusions where the number of centroids 3 and 4 have a better iteration of values than the number of centroids that increasingly high and low based on the iris dataset.

At present, there are many Information Systems Development methodologies. However, we have to select the suitable one related to the problems. This paper presents an implementation of the Dynamic Systems Development Methodology (DSDM) and Object-Oriented (OO) as two combine methods to develop an application of billing in a mental hospital (study case in Indonesia). The application allows the management of the mental hospitals to control and evaluate patient services, and it supports decision-makers for improving the organization. Based on literature studies, we obtained the suitable two methods for DSDM adjusted to the resources, the time frame, the goals, and the required functionality. Meanwhile OO is a highly iterative approach. Data results of the interviews, questionnaires, observations, and artifacts were analyzed according to the user requirement process. The study can be concluded that DSDM and OO method is effective in developing an application. The paper depicted problems in facts finding.

Naïve Bayes is a prediction method that contains a simple probabilistic based on the application of the Bayes theorem (Bayes rule) with the assumption that the dependence is substantial. Classification is a technique in data mining to form a model from a predetermined data set. Data mining techniques are the choices that can overcome in solving this problem. Therefore, researchers make a comparison of Naïve Bayes by modifying using PCA. Improving the comparative performance of the Naive Bayes method by weighting using Principal Component Analysis (PCA) and Naive Bayes was carried out in this study. Research conducted on the classification model of Naïve Bayes (PCA + Naïve Bayes) using the Iris dataset that simplified into two attributes, four classes and 147 instances with an accuracy rate of 97.78% with a classification error rate of 2.22%. Meanwhile, the Conventional Naïve Bayes classification model uses four attributes with four classes from the Iris dataset, which has an accuracy rate of 95.45% with a classification error rate of 4.55%. Based on the test results of the classification model, it can be concluded that the success of the PCA can be used as a reference to improve the accuracy performance of the Naïve Bayes classification model.

Finding the shortest path in direction effective is essential. To solve this shortest path problem, we usually using Dijkstra or A* algorithm. These two algorithms are often used in routing or road networks. This paper's objective is to compare those two algorithms in solving this shortest path problem. In this research, Dijkstra and A* almost have the same performance when using it to solve town or regional scale maps, but A* is better when using it to solve a large scale map.

This research conducted to simplify and eliminate attributes or features that are less relevant without reducing the intent and purpose of the original data using Principal Component Analysis (PCA) to improve the performance (accuracy) of the K-NN (K-Nearest Neighbour) classification method. Modifying the method yields an average accuracy of 88%, where the K value is at K = 3 to K = 9. While the lowest accuracy value generated from K-Nearest Neighbors Conventional with PCA + K-NN classification models for the Pekanbaru Air Quality dataset has an average accuracy of 87% where when the K value is at K = 2, K = 4, K = 6 and K = 8. The highest average error is 0.11% where when the value of K is at K = 2, K = 4, K = 6 and K = 9. While the lowest average error value generated from K-Nearest Neighbors Conventional with PCA + K-NN classification model of the Pekanbaru Air Quality dataset is 0.08% where when the K value was at K = 5.

The RSA public key cryptosystem was among the first algorithms to implement the Diffie-Hellman key exchange protocol. At the core of RSA's security is the problem of factoring its modulus, a very large integer, into its prime factors. In this study, we show a step-by-step tutorial on how to factor the RSA modulus using Euler's factorization algorithm, an algorithm that belongs to the class of exact algorithms. The Euler's factorization algorithm is implemented in Python programming language. In this experiment, we also record the relation between the length of the RSA moduli and its factorization time. As a result, this study shows that the Euler's factorization algorithm can be used to factor small modulus of RSA, the correlation between the factoring time and the size of RSA modulus is directly proportional, and better selection of some Euler's parameters may lead to lower factoring time.

Medan is the capital of the province of North Sumatera, Indonesia. Medan city is known as a city that has a lot of old buildings heritage legacy of the former Dutch. It is unfortunate as a result of the lack of maintenance and attention from the government and community making the historic buildings gradually demolished and replaced with new buildings. By using Image-Based-Modelling in the process of making 3D buildings. This application of Augmented Reality Tour is expected to be a recognition media, and can increase the interest in studying history.

Study of Land suitability using Geographic Information Systems (GIS) is a way to determine the location for many fields, including in the defense field. The Sunda Strait is part of the international shipping route where there are several cases of international smuggling in this region, so that it becomes a concern for Indonesia defense. The concept of marine defense by applying Radar is something must be done at this time. Over The Horizon (OTH) Surface Radar is a type of High-Frequency (HF) radar with a detection distance that goes beyond the earth horizon. Research on OTH Surface Radar Placement is something that can be done at this time, considering Indonesia has not applied it at this time. The method used in this study is to determine the best placement by comparing the parameters of two types of OTH Surface Radar that have been used in other countries to determine the criteria of placement parameters. The analysis process will use the Analysis Hierarchy Process (AHP) by determining the importance of the parameters for OTH Surface Radar Land Suitability. The GIS process is carried out using the Overlay method which is used to determine the suitability based on a matrix of geographic parameters obtained between weight and class. The result is one suitable location to be the main area in the placement of OTH Surface radars for defense in the Sunda Strait located in the district of Pulo Merak, Serang Regency.

Indonesia, which is the world's most populous Muslim-majority nation, Islamic education is not an alternative to secular education but compulsory to any Muslims learn the way of life. The two primary sources of the religion of Islam is the Quran and Hadith. These two are where the majority of the teachings come from. However, when looking for guidance, a Muslim often refers to Islamic scholars to interpret the verses and hadith for them and educate themselves on a topic. However, due to many circumstances, people could not meet and ask a scholar personally regarding Islamic jurisprudence. Chatbot is one of the solutions. Chatbot offers users new opportunities to improve the learning and engagement process, reducing the typical cost of face-to-face consultation. However, to train a chatbot on Islamic Jurisprudence, a text classifier is needed to build a strong knowledge base for the chatbot. This study adopted a standard methodology for building a text classification model. This study used 600 Islamic jurisprudence text data obtained from the books and the web written by an influential Islamic scholar named Ustadz Abdul Somad (UAS). Machine learning algorithms such as Bayesian Network and Naïve Bayes, were employed to classify the text data. Based on the experimental testing results, the Naïve Bayes algorithm is more accurate in all evaluation models, 84.25% using training set, and 76.54% using 10-Fold cross-validation. Meanwhile, the Bayesian Network algorithm is faster in terms of time taken on all evaluation models. Thus, it can be concluded that the text classification model using Naïve Bayes and String to Word Vector filter have the potential to be used effectively but still has plenty of room for improvement.

Municipal Solid Waste is an endless problem because as long as life is still running, waste will always be produced. Batamcity shows that there is poor scheduling of transportation of garbage from community settlements to temporary collection points (TPS) to the final disposal site (TPA) of Batam City. The study aims to optimize the number of waste transporters by applying a genetic algorithm. In this study, genetic algorithm can optimize the number of Batam City TPS transporters based on the number of TPS per district, the volume of TPS, and the distance between TPS to TPA. The number of waste transporters available in Batam City in dump trucks, arm rolls, pickups, and motorized pedicabs are 54, 44, 100, and 40 respectively. The result determines the optimization numberof waste transporters with a genetic algorithm succeeded in making the volume gap as small as possible, particularly 15.96% with the target volume of waste transportation and reducing 26.38% of the average gap in the actual volume of waste transportation. In addition, the non-transportable wastevolume optimally by using dump trucks, arm rolls, pickups, and motorized pedicabs is 58.92, 120.21, 346.31, and 380.74 ton respectively.

This paper is an academic study that discusses how to design air defense missile modeling and simulation, as a missile development strategy for the Indonesian National Army. Aerodynamic is the most important part of missile development, which regulates lift, drag, thrust and other parts that interact directly with air. The success of developing a rocket that has reached level 7 technology mastery readiness (Prototype Tested), can be a starting point to seriously initiate the development of Indonesian Missiles. The initial design process was based on the specifications of the 122 mm caliber defense rocket, the length of 2810 mm, the weight of the 60.8 kg rocket and the 15 kg warhead with an overall range of 30.5 km that would be adjusted to the initial configuration of the air defense missile. Aerodynamic testing will be carried out on Solid Work, Ansys and Missile Datcom software which will be compared with the results of each other. This development strategy can optimize the rocket products that have been successfully developed by Indonesia, because the sustainability of the rocket mastery will be very useful to be used as a basis for missile development, specifically in terminal air defense missiles, which is the weak point of Indonesia's air defense today.

At one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past few years. Facial recognition technology (FRT) has emerged as an attractive solution to address many contemporary needs for identification and verification of identity claims. It brings together the promise of other biometric systems, which attempt to tie identity to individually distinctive features of the body, and the more familiar functionality of visual surveillance systems. This report develops a socio-political analysis that bridges the technical and social scientific literature on FRT and addresses the unique challenges and concerns that attend its development, evaluation, and specific operational uses, contests, and goals. It highlights the potential and limitations of the technology, noting those tasks for which it seems ready for deployment, those areas where performance obstacles may be overcome by future technological developments or sound operating procedures, and still other issues that appear intractable. Its concern with efficacy extends to ethical considerations. Face recognition technology may solve this problem since a face is undeniably connected to its owner except in the case of identical twins. It's nontransferable. The system can then compare scans to records stored in a central or local database or ever on a smart card

Recently, cloud computers are widely used due to the development of computing environment and network speed. Unikernel is considered to be an attractive operating system in the manycore environment that effectively provides cloud computers. HalVM is a unikernel coded in Haskell. In this paper, we analyze the performance of Haskell running in a unikernel, which has shown good parallel programming performance in a manycore environment. In this paper, we analyze the performance of Haskell running in a unikernel, while Haskell has shown good performance in a manycore environment. To do this, we select HaLVM as the target operating system and analyze the performance by testing various Haskell parallel programming models. Test result shows that HaLVM is scalable only on IVC. We also implement a library to make programming with IVC more convenient, and use this library to compare extensibility experiments. Our test shows HaLVM's scalability is 112.42% higher than Linux environment.

Confidentiality and size of data are some significant aspects in data exchange. Public key encryption algorithms, such as El-Gamal is known as to preserve confidentiality. On the other hand, public key encryption algorithms tend to increase the size of the encrypted data, making it difficult to transmit to the other party. This research will combine the ElGamal public key encryption algorithm with Even-Rodeh codes. ElGamal is used to secure data and Even-Rodeh codes are used to compress data. The parameters is being tested are the compression ratio and space savings. In this research, we will do an experiment that includes some data texts from Artificial Corpus. The results show that the crypto compression system can reduce the size of the transmitted data and the transmitted data could be revert back to the original data while still maintains its confidentiality.

The absence of requirement documents or incompatibility of the requirement documents with existing software can be a problem in developing or maintaining software. Without knowing things that become requirements can cause software as a product that fails because it does not meet customer desires. One of the main problems in developing or maintaining software is that developers do not know the entity relational schema of the software. So developers will prefer to rebuild from scratch. This paper discusses database reconstruction from SQL to entity relational diagrams by identifying the primary and foreign keys of SQL sampling.

Data compression was born as a solution to human needs for digital data. This research compares two compression algorithms, namely the Start-Step-Stop code algorithm and Gopala-Hemachandra codes 2 (GH_-2 (n)) algorithm in the case of text file compression. compression ratio (CR), space savings (SS), bit rate and running time are calculated in the test as consideration to compare the advantages of both algorithms. Tests carried out using homogeneous strings, heterogeneous strings and artificial corpus. In homogeneous string compression, both algorithms have the same advantages because the value of CR, SS and bit rate are the same for each number of strings used. From the time of compression, Start-Step-Stop algorithm faster than the Gopala-Hemachandra algorithm. Testing of heterogeneous strings found that the Start-Step-Stop algorithm is superior to the Gopala-Hemachandra algorithm because it can save more storage space.

Data security becomes an important thing in the computer era nowadays, especially in digital lock. Because of easy to use, there is a lot of digital locks connected to Android smartphone. However, the security of digital lock is lower if commands and passwords exchange is unprotected. That is why algorithm combination concept is important to be applied. Vigenere Cipher and XOR Cipher algorithm combination is simple to be applied, where both are symmetric cryptography algorithm which has advantage in short calculation time, so the plaintext processing can run quickly. To implement the cryptography algorithm combination concept, a digital lock prototype is also needed. One of the best microcontroller for prototyping is Arduino UNO. It can communicate with other devices through Bluetooth connection especially Android smartphone if connected to Bluetooth module. The Arduino UNO based digital lock will communicate with Android smartphone via an application in the smartphone. It is found that Vigenere Cipher and XOR Cipher algorithm combination, and also other support algorithms can improve the secrecy of communication between devices in the digital lock system.

Driving simulator is one of important system for driving behavior studies. It offers a replicable virtual driving environment and it has possibility to create a various scenarios to carry out in real environment. The problem in development of this simulator is how to reduce a prices in certain point areas have made it possible to create low-cost driving simulators, but with the features that are usually found only in expensive driving simulators. This article is presented a low cost PC-based driving simulator. The aim is to use the simulator as a platform for studies of the driver's behavior. The complete simulator is using three 27" LED screen, handle by a standard PC, typically used for computer games. As Input we using steering, pedal and shifter G29, with force feedback. For software we using city car home edition as tools to measure validity user and developing simulator to driver's behavior study.

Arranging the sequence of places to visit is the common problem that tourists or foreigners encountered when visiting a new site, especially for foreigners that visit Medan City. This kind of case similar to Traveling Salesman Problem cases. Therefore we could use one of the modified TSP algorithm to solve it, which is Modified Cheapest Insertion Heuristics. The Modified Cheapest Insertion is a method to insert the cheapest weight starting from 2 points of place until all of the sites are being connected from the starting point until the endpoint. The strength of Modified Cheapest Insertion Heuristics is the calculation will remain stable even for a large number of inputs. In this research, all of the desired-to-visit places are being connected as a route.

This research aims to design medicine information based on the ontology scheme and to display the relationship between information through chatbot as search media. The diversity of information does not guarantee to gather a relevant search result with user's needs. A conventional search engine would be substantially beneficial in information searching yet could not able to comprehend meaning of found information and its relationship with other information. However a machine could understand the relationship and the meaning of information through the implementation of semantic technology, which is ontology. Ontology is implemented to represent semantic metadata information. The information designed with the ontology model would be very assistive in searching for data which is relevant to users' need. The result of implementing ontology as a knowledge base in this research able to display the information of a disease and its relationship with medicine used as the medication for such a particular disease. The evaluation of our system shows that 90% of queries from users generate a valid response from the chatbot. Therefore, this research could be used as a reference in search of medical information and describe its relationship with a particular disease or related to medicine.

In software development, either alone or in a team, there are many aspects that determine the success in developing the software, including each developer's skills. Studies show that the application of metacognition can increase the effectiveness and efficiency of software development. To measure a metacognition skill, there need to be a metacognition measurement tools. One example of this measurement method is adapted engineering design metacognitive questionnaire. However, the respondents feel that existing tools still have not given them any benefits. This research is conducted to develop an information visualization tools for the metacognition measurement from an adapted engineering design metacognitive questionnaire. The research was performed using qualitative method adapted from the user-centered design approach, which is user requirement analysis, design alternatives, prototyping, and evaluation. The finding suggests that with information visualization, the students as the respondents feel the benefits of filling the EDMQ questionnaire. However, from the design standpoint, there are still numerous things that can be improved to make the visualization more informative.

This study aimed to analyse the background of drug abuse users to provide an overview of drug abuse patterns in particular with sampling from North Sumatera, Indonesia. Data was obtained from several Medan Rehabilitation Centers. K-means clustering model was selected for data modelling. The results of the algorithm showed which city has the highest drug abuse users and the educational background of drug abuse users.

The efficiency of network administrators have been decreased concurrently due to complexity and heterogeneous of network built in certain environment of company. Actually, large heterogeneous network has created a crisis and conflict for many organizations. Available network tools and solutions are not only expensive but also difficult to install, configure, manage and maintain. This paper discusses the implementation of network fault in the service industry to match with the expectations of stakeholders to be able to achieve the higher efficiency and to carry out proactive processes although the practical truth is often the opposite way.

Common problems in service delivery is might related to the issue of timing, marketing cost, user experience, generating lead, identifying prospect, forecasting demand, value proposition, security, privacy, identity management and many more. Unfortunately, company often decided on the wrong context and concept lead to misrepresentation and misinterpretation on the requirement for the service improvement. Thus, the direct intervention through certain criteria in the characteristics and attribute of service delivery should be conducted with judgment assessment. It is done in order to identify the target and examine the policy used to support the outcomes. Thus, this study explore the model used for particular company, which in this case NetHost to provide insights on how the assessment can be fruitful in the long term investment for intangible aspects of service delivery.

Privacy paradox can be defined as the implication at the high intense interaction as the customers and market demand over the utilization of IT to provide online type of persona as the representative of certain people in the digital life while simultaneously protect their identities against potential threats but at opposite way lead to improper use of the system. Thus, this study want to explore the paradox exist in the process of protection the personal data in utilizing service or features in the electronic platform.

This research aims to study the efficiency of two variants of variable-length codes (i.e., Yamamoto Recursive codes and Punctured Elias codes) in compressing texts. The parameter being examined are the ratio of compression, the space savings, and the bit rate. As a benchmark, all of the original (uncompressed) texts are assumed to be encoded in American Standard Codes for Information Interchange (ASCII). The overall result shows that the Punctured Elias codes are consistently more efficient to compress texts than Yamamoto Recursive codes.

Image is a form of visual data or information that is often used today. Sending data or information can be done in various ways and anyone. However, not all contents of existing information are public. It is not uncommon that information is misused by irresponsible parties. For this reason, security is needed for confidential information. This image security can be done with Steganography Technique. Steganography technique is a method for hiding information in an image. The method used is the LSB (Least Significant Bit) method. Where every bit lowest in the image media bytes will be replaced with the message bits that will be inserted. The bit used is the last bit of the RGB binary. The goal is that the message sent by the sender cannot be known by a third party, and can arrive safely to the recipient of the message. To make the confidentiality of messages more secure, it is necessary to hide the existence of messages to overcome the weaknesses of the LSB method used, so the authors combine them with the RSA RPrime algorithm (Rivest Shamir Adleman) for the encryption and decryption process. The security of the RSA RPrime algorithm lies in the level of difficulty in factoring non prime numbers into prime factors. The longer the key bits, the more difficult it is to solve because of the difficulty of factoring these two very large numbers. The results showed the test using a document file 2.93 MB with cover image size of 5760 x 3840 pixels, where in the larger the file inserted, then the time of encryption and decryption process is also long.

Tuberculosis is a disease caused by a bacterium called Mycobacterium Tuberculosis. Most Tuberculosis bacteria not only attack the lungs, but also attack other organs. Tuberculosis disease can spread and contaminate through the salivary and bacterial when the sufferer coughs and sneezes. Thus, the contagion of tuberculosis can take place either through contact directly with the sufferer or through the air. The examination system of Tuberculosis is still done manually. Therefore, a computational method is necessary to examine and identify Tuberculosis suffered by the patient through X-ray images of human lungs. The method used in this research is the Extreme Learning Machine. Lung X-ray images are used as input for image processing. The steps taken before identification were image pre- processing and Thresholding. The external results of this research include HKI in the form of software (registered), international conference presenter (done). In addition, the results of this study can assist public in determining the types of tuberculosis suffered so that it will be more efficient in early treatment of the disease.

The need for disaster preparedness becomes very important in Indonesia. Due to its geographical situation, within a ring of fire, Indonesia is prone to several disasters such as earth-quake and volcano eruption. This paper presents the design of a context-aware system to pre-emptively notify and provide some information to the population around Merapi volcano. The information contains some dangerous area and safe-place/shelter based on the user location. The proposed design can also notify the level of danger that might be encountered by the user and the mitigation path within a certain distance.

Milk is one of the most preferred and most easily absorbed nutrients. This drink naturally contains important nutrients, such as vitamins A, D, B12, protein, calcium, magnesium, phosphorus, and zinc, and others. Milk is also beneficial for children and adults. Starting from maintaining healthy bones and teeth, as a source of energy, and so on. In Indonesia, especially on the island of Sumatra, fresh milk production is carried out by cattle and goat farmers in cooperation with milk companies. This research have a purpose is to predict the production of fresh milk on the island of Sumatra so that the local government, as well as cattle and goat breeders on the island of Sumatra, have benchmarks to further increase the production of fresh milk in their respective regions in the future. The method that will be used in this research is Deep Learning Cyclical order which is the development of ANN. The research data used were data on the production of fresh milk on the island of Sumatra in 2009-2018 sourced from the Indonesian Statistics Agency. This research will be analyzed using 3 network architecture models, namely 4-5-1, 4-10-1 and 4-5-10-1 with the best network model chosen is 4-5-10-1 with an accuracy level of 90% and MSE value of 0.0157179042. Based on this best model a prediction of fresh milk production in Sumatra will be carried out in 2019-2020.

Augmented reality is one of the interactive technologies that can be used to help the user to easily interact with the system. The game application called AR Virtual Pet Simulator is a simulator game which uses Augmented Reality technology to display a virtual pet, for the purpose of enhancing the users' experience. Users can also interact by using application to understand the daily behaviours of pets. Application development methods are carried out starting from gathering requirements, design, implementation, to testing and evaluation. Results from the end evaluation shows that the application was well-liked by users and it could help users in knowing how to take care of pets, but the experience of using the application is not the same as having a pet in the real world. Conclusion gathered from the research is that applications with virtual pets are not able to entirely replace real pets but are able to provide knowledge on taking care of pets. Where users cannot interact directly with pets.

The Faculty of Computer Science of Universitas Indonesia has implemented online learning facilitated by a learning management system called Student-Centered E-Learning Environment (SCeLE). One of its important features is the online discussion board that enables students to construct knowledge collaboratively. Connecting and comparing several ideas in an online discussion forum are challenging for both students and teachers, especially when the discussion runs very fast with long messages. This study proposes an online collaborative mind mapping feature integrated to the discussion forum. A prototype was developed using the Go programming language and Gin web framework. The usability testing was employed to gather data about user experience in using the application. The participants of the study were all students of the Faculty of Computer Science of Universitas Indonesia. The result of the study shows that the application benefits most of the users. The participants acknowledged that the features help them follow the discussion and it supports the collaborative work. However, in terms of the design and the user experience, more works are required to improve the feature needs.

Data that has many attributes or higher dimensions will affect the performance of the K-NN classification algorithm. In this study, the Gain Ratio implemented for selecting and reducing the dataset attributes to form a new dataset for the classification process is carried out with the K-NN. The dataset used in this study are the Breast Cancer Coimbra dataset and Hepatitis C Virus dataset obtained from the UCI Machine Learning Repository. The results showed that the Breast Cancer Coimbra dataset, Gain Ratio can improve the performance of K-NN with average value 0.535596 TPR, TNR = 1, NPV = 0.608279, FNR = 1, FOR = 0.391721, Accuracy = 72.85%. In Hepatitis C Virus dataset also managed to improve the performance of K-NN with average value TPR = 0.665596, TNR = 0,876667, NPV=0,738279, FNR=0,88, FOR=0,521721, and Accuracy=86,25%.

This research concerns on the influence of higher order solution to nonlinear evolution of bichromatic waves based on Benjamin Bona Mahony (BBM) equation. Asymptotic method was applied to determine the solution expanded to the fifth order. In previous researches, this method was applied on the same equation to find its solution up to the third order and it was obtained that the waves underwent deformation and amplitude amplification affected by the occurrence of a pair of side bands during their propagation. In this study, the effect of the higher order solution on the increasing amplitude was observed. A quantity called as Maximal Temporal Amplitude (MTA) was measured to find the maximum position where the highest amplitude occurred and the Amplitude Amplification Factor (AAF). MTA gives information about the waves' highest elevation at every spatial position during the observation time. The analysis includes comparison between the third and fifth order solutions in their contribution to the rise of the amplitude and the maximum position.

Parking space is one of the most critical needs of people's lives, especially in Indonesia. According to the Central Statistics Agency, vehicle growth in Indonesia in the last ten years is 9% per year. Meanwhile, parking needs are being eroded by settlements, shops, and public service buildings. Limited parking lots make it hard for drivers to find available parking spaces. When looking for a parking space, it was causing impacts such as traffic jams, air pollution, causing noise and panic. The intelligent parking system is the solution to this problem. This system can provide information on available parking slots. In this study, parking locations are marked with a circle. If a circle is visible, then a parking lot is available, and if not, then the parking location has been filled by the vehicle. Circle objects in images taken using the camera can be identified by the Hough transformation method or feature extraction. These two methods are compared to measure the accuracy and speed of the process. Experiments and observations on the performance of both methods show that both methods can recognize the location of the available parking slot. The feature extraction method has a better detection speed with an average processing time of 1.1 seconds. The Hough transformation algorithm has an average processing time of 4.1 seconds. Then it can be concluded that the feature extraction method is better applied to the smart parking system.

The risk that could happen in operating heavy machinery, such as excavator, can be avoided by doing special training to the operator. The operator of an excavator can learn the use of each joystick and lever in excavator by using a virtual reality without worrying about any damage. A virtual reality controller, such as Leap Motion Controller, can improve human computer interaction. To get a result of user experience in an excavator simulator, a survey of user agreement level and user satisfaction is required. The result of this research is none of the statements in the survey has an average score of 4.

Precise positioning plays an important role in the construction of intelligent coal mines. However, existing precise positioning methods often have problems with long positioning period, limited positioning capacity and low precision. To overcome these shortcomings, this paper proposes a time-division downlink time-difference-of-arrival (TD-D-TDOA) positioning method. In the proposed method, the base station first implements clock synchronization with the reference clock by direct or relay. Then the base station allocates the time for transmitting two positioning messages according to its serial number. Finally, the label uses these messages to obtain the TDOA and its location information. The proposed precise positioning method has the advantages of millisecond positioning cycle, self-position calculation, unlimited positioning capacity and high positioning accuracy. Moreover, the tag only needs to receive the location information broadcast by the base stations in the positioning process, which reduces the coupling degree between the tag and the location base station, as well as the cost of the tag hardware. Experimental results demonstrate that our method has a positioning accuracy of less than 20cm and a positioning frequency of up to 20 times per second, while also having high positioning stability.

ICT has enabled democratic process to be more transparent and enabled citizens' participation in the election process. However, public trust is a mandatory requirement for a good democratic transition. Participation in monitoring election process could be implemented as a crowdsourcing effort to improve public trust in the election result which in this article based on a case study of KawalPilpres to monitor 2019 Indonesian presidential election. Trust factor is a key success for monitoring effort. Therefore, data quality becomes necessity. Data quality is assessed using Loshin's maturity assessment and analysed using Loshin's improvement strategies. Based on our assessments, there are three top categories for improvements namely governance, expectations, and policies of data quality management.

Anatomy is not only can be learned by reading a text book, but also by using an interactive system, such as virtual reality. In this paper, an anatomy learning system using VIVE Controller has been developed. User agreement survey and user satisfaction surveys are required to determine the interactivity level of VIVE Controller in the system. The result of this research shows that users agree that using VIVE Controller in anatomy learning system in virtual reality environment is very interactive with an average score of 4.33. The result also shows that users are satisfied using VIVE Controller in this system.

Automatic Speech Recognition has penetrated deeply into our life. For well-resourced language, it can be considered as solved, but that's not the case for under-resourced language like Bahasa. Although it's the 7th most spoken language in the world, the research of speech recognition for Bahasa was still extremely limited, with setting still inconvenient for the real world and industry. This research is an attempt to make a speech recognition model that has applicability to the real world and industry, specifically that supports sentence level input with variable character length with end-to-end training. We built the model using the deep learning approach, specifically utilizing the residual networks and Bi-Directional Gated Recurrent Unit (Bi-GRU). To the best of our knowledge, this is the first Indonesian ASR model that can be trained in an end-to-end manner. Our model surpassed the baseline model on all metrics and achieve competitiveness with the current best result, which used the visual modal, for the dataset even with a more difficult and prone to noise modality like sound.

Uang Kuliah Tunggal (UKT) is a portion of the single tuition fee that is borne by each undergraduate student at a state university in Indonesia. UKT is the number of fees that have to be paid by students in each semester. Basically, UKT is implemented to impose tuition fees according to the income and the condition of students' families. However, there is an issue in regard to the inappropriate classification of UKT. This issue is caused by several factors such as manual method is still used in determining UKT Classes and there is likely an element of subjectivity in determining UKT Classes of new students. Based on these issues, a decision support system that can determine UKT Class of new students is needed. The Naïve Bayes Classifier (NBC) method is used to classify data into eight UKT Classes. Whereas Fuzzy-TOPSIS is used in the optimization selection process of UKT Class 1 to 8. This method was chosen for its capability in choosing the best alternative out of several possibilities, in this case, the intended alternative is the most suitable new student to be selected in UKT Class based on six predetermined criteria. Research results show that the NBC Model can identify UKT groups of students with mean values of precision and recall testing are 77.8% and 77.8% and the model accuracy is 77.8% as well. In optimization selection process of UKT using Fuzzy-TOPSIS results obtained the percentage of UKT 1 group recommendations was 5.33%, UKT 2 was 5.33%, UKT 3 was 10.22%, UKT 4 was 24.89%, UKT 5 was 24.89%, UKT 6 was 10.22%, UKT 7 was 10.22% and UKT 8 was 8.00%. Based on the results above, it can be concluded that the combination of Naïve Bayes Classifier and Fuzzy-TOPSIS can be implemented for determining the UKT Classes. Then the recommendations of the UKT Classes can be considered in determining the UKT Classes of students for the Decision-maker.

With the development of increasingly affordable smartphone technology that is owned by almost everyone, making some activities can be done only by using this device. Smartphone computing capability that is quite powerful, accompanied by various sensors embedded in it, allows the smartphone to be used as a measurement device in various fields of research. This article tries to review the use of smartphones as a measure of one's mentality by conducting a meta-review of several review articles that have been done before. This article tries to look at research trends that measure a person's mental state by using sensors found on smartphones and also to help researchers decide on topics to explore.

IndoAcro is an Indonesian acronym and expansion repository created using machine learning and big data technology. The repository can be publicly accessed from www.indoacro.cs.unsyiah.ac.id. Six important steps of IndoAcro have been developed and implemented, which consists of (1) data crawling, (2) data cleaning, (3) generating candidate pairs of acronym and expansion, (4) generating numerical features, (5) classifying the candidate pairs, and (6) filtering the classification results. In this study, we introduce and analyze the implementation of data auto-update for IndoAcro. Since it was developed, IndoAcro has 2,232 pairs of acronym and expansion, collected from more than 50 thousand online news articles. Because no auto-update approach has been implemented previously, the number of acronym and expansion pairs in the database is monotonous, dull, and static. In this study, we introduce and analyze the implementation of data auto-update for IndoAcro. We have analyzed and evaluated the data auto-update process for 180 days, each process consists of 2 days interval. We found that the data auto-update approach has successfully implemented and updated the data for IndoAcro. We collected 1,639 pairs of acronym and expansion in the first run, 343 and 224 pairs in the second and third runs.

Humans are basically curious creatures. We always look for all the latest information through books or news. News usually contains tags or categories to make it easier to find similar news. It can be done manually by a human or with a machine to make it easier. Data mining techniques such as clustering and classification can be used to help the categorization process. Clustering is a technique that can be used to grouped news based on their similarity. There is some algorithm that can be used to clustering data. One of them is Ant Colony Optimization (ACO). ACO is a metaheuristic algorithm that mimics how ants bring food to the colony. ACO also can be used to solve the clustering problem. In this paper, we will use the ACO version for clustering to cluster news and find the performance of the said method. Then we compare the result with ground truth.

Single Nucleotide Polymorphism (SNP) is a form of Deoxyribonucleic Acid (DNA) variation that can be used in predicting phenotypes. Data quality control is a crucial stage in the process of detecting phenotypes using SNP data. In this study, we built a web-based application to carry out the SNP data quality control function. Raw SNP data in string type are filtered by calculating the missing rate, minor allele frequency, and Hardy-Weinberg Equilibrium values. The result is SNP data that has been filtered in numeric form, namely the value 1 represents dominant homozygous, 2 represents heterozygous and 3 represents homozygous recessive. SNP encoding in numerical form aims to make SNP data can be processed into machine learning for the further phenotype prediction step.

Centroid is the central point of data in the grouping process, it is necessary to analyze the centroid in determining the initial value in the initial clustering process. So it is used as a cluster center point in the X-Means algorithm clustering process. Determine cluster center points or centroid, measure the performance of the X-Means algorithm with range cluster parameters by measuring distances between centroid for a fast and efficient way to group unstructured data, and to speed up the model construction process and divide several centroid in half to match the data as a test tool for the analysis of the X-Means method. From testing using the X-Means algorithm with the determination of the number of Centroid clusters carried out by modifying the X-Means method to do some determination of the centroid to get the results of 11 iterations. From the results of these tests produce good cluster members the level of similarity of data with other data and in determining the number of clusters, using the modification of the Euclidean distance method, get better results of the similarity level of each member compared to randomly determining the number of clusters with several iterations.

Labuhanbatu Regency is a regency located in the North Sumatra province of Indonesia. This regency is crossed by a national road across Sumatra that connects provinces on the island of Sumatra. This has led to an increase in traffic accidents in this region. The number of accidents reached 114 accidents in the official police report for 2018. This study discusses locations that have a high frequency of accidents and represents them in the form of spatial data. The data used is based on the official report of the accident from Labuhanbatu Resort Police in 2018 which consists of 3 attributes namely, accident id, time of the accident, and location of the accident. The method used is to create a density map to calculate complexity in certain areas using Quantum GIS. This study uses the Kernel Density Estimation (KDE) method with a search bandwidth in an area of 300 meters. The results of the study are accident heat maps for the study area and related to the inputted attributes. The highest heatmap in the Bilah Hilir and Panai Tengah sub-districts with 25 attributes and 24 accidents included. The use of heatmap can produce spatial data that is easier to understand because it's clustering from the same area. In this study, clustering is done based on the time of occurrence to obtain a heat map in red to black for the density level based on the frequency of accidents.

In everyday life, smokers are often found around us. As we know, a lot of losses caused by cigarette smoke and cigarette smoke itself can also disturb the people around us. In order not to disturb the health of others, there are restrictions in certain rooms for smoking by giving a sign that smoking is prohibited. But some people sometimes ignore the ban. In this study, our system was embedded to give warnings to people who smoke in rooms that cannot smoke. The system will sound the siren if smoke is detected. This system is designed using a STM32 microcontroller and MQ-2 sensor to detect cigarette smoke. From the results of testing the system will work well by directly giving a signal when there is cigarette smoke.

In this study using two methods, namely Sugeno Fuzzy Logic and Levenberg-Marquartd methods. The data to be used is data from used Toyota Avanza cars for Medan and surrounding areas. The use of the fuzzy method in this study is based on its superiority in solving vague problems so that it is considered to be suitable for the condition of a used car in which each unit has different conditions. The results of the use of Sugeno fuzzy data obtained will be used as input into the levenberg-marquardt (LM) network which has a fairly good ability to perform calculations, especially to predict an output with a more efficient time. LM produces an output with a small Minimun Square Error (MSE) value of 3.64 in testing with 9 hidden layers. On the other hand, to analyze the resulting error, a comparison is made between networks that have 9 hidden layers, 27 hidden layers and 81 hidden layers with the smallest MSE results obtained on a network with 9 hidden layers.

Indonesia is one of the countries with high plant diversity. Almost every region in Indonesia has distinctive plants and may not be present in other countries. Based on these facts required a strategic step to record and identify plants in Indonesia. One method that can be used to leaf image feature extraction is the Gray Level Co-occurrence Matrix (GLCM). This research will implement k-Nearest Neighbor (k-NN) method to classify type of plants based on leaf texture. The classification result based on GLCM using k-NN classifier showed that the accuracy using k = 3 was 83%. The use of parameter k influence classification results, the greater the value of k then the accuracy would be smaller. Classification errors for some types of leaf images occurred because the value extraction traits generated by GLCM was very similar and had a small range of values.

One of the negative impacts of the development of the era of digital technology on communication media today is the damage and loss of information data. Access to communication media is a means of delivering information that is vulnerable to manipulation. Therefore, cryptography is used to keep the information confidential. Cryptography is an art in encoding messages into other forms so that the message cannot be read by unauthorized parties. Tiny Encryption Algorithm (TEA) algorithm is a symmetric cryptographic algorithm in which the key is divided into four subsections and uses 128 key bits and operates 64 bits of data blocks and then divided into two blocks into 32 bits during the encryption process. In order to make the encryption stronger, it is combined with steganography where the steganography method used is Least Significant Bit (LSB) which has the function of inserting data into the last bit of other data. Linear Congruential Generator (LCG) is a random number generator in the LSB method where its function is as a flow of inputting data that has been encrypted randomly into another data as a cover so that the combination of these methods becomes Modified Least Significant Bit Pseudo Random Number Generator. The combination of cryptography and steganography is able to create a security in sending a confidential message to be safer.

Understanding of characteristics can be assessed either by public decision-makers, who have been the primary concern of political actors or by voters themselves, who have participated directly in the process of election. Therefore, this study focused on the voters' self-evaluation to look out on the voter decisions with survey questionnaire have been used as the tools to collect the data independently in relation to create formative measurement model. In addition, major influences to the public also involves the role of emotion, political socialization and tolerance to the diversity of media views. This study investigated gender-based patterns of 790 samples using PLS as a data analysis tool, which found interesting result, which suggested that Social Norm (SNorm) have strongest effect to both PCon and PBen with 0.179 and 0.066 respectively followed by Technology Solution (TSol) with 0.057 and 0.022 as well Legal Regulation (LReg) with 0.043 and 0.020 accordingly. Thus, in the developed model, the researcher recommend that social factors can lead to determination of demand and participation in the voting to have public confidence and good behaviour in the protective manner.

The present scale of computing inevitably demanded increased level of data security, which is the concern of cryptography. Security of the cipher depends on the strength of the key and the algorithm used to generate the keys. Many modern cryptographic algorithms are based on Number Theory, but in recent years an alternative approach has been studied which is based on Chaos Theory. Many properties of chaotic systems such as nonlinearity, randomness, and sensitivity to initial conditions bear resemblance to those required by cryptography such as diffusion and confusion. Implementations of chaos-based cryptosystems have been proposed by other researchers and yet the strength of these systems from a cryptographic point of view has not been thoroughly considered. This paper discusses the appeal of chaos-based cryptography, some of the researches already done, and the challenges that this approach faces to be established as a fully secure method for data security.

The adoption of e-voting in several countries poses certain challenges, which are very similar when electronic means are applied to any activities, such as e-governance or e-commerce. Therefore, some people due to economics, politics or social reasons expect the e-voting use will facilitate and solve previous election's problem. Unfortunately, the most complex and difficult practical implementation with distinct problems depends on the particular condition or culture. One of essential factor concerning the adoption related to privacy protection. Thus, this study examines the relationship of perceived benefit and privacy concern towards personal data protection by establishing model of formative measurement. For the generalization purposes, a survey questionnaire consists of 4 categories of 45 items was distributed offline and online to approximately 800 people with purposive sampling in selected multicultural cities in Indonesia. The result suggested that the Perceived Benefit (PBen) has the strongest predictive value of ƒ² and Q² compare to Privacy Concern (PCon) with 0.212 and 0.083 respectively.

Clustering is a method needed to group data or objects based on the required level between data, K-means is one of the clustering methods used that can be used easily in its implementation, there are some additions to this method according to the data center and on the weighting of the distance between data, the weighting of the distance between data on K-Means traditionally can be done using Euclidean Distance, Canberra Distance and Manhattan Distance, making this an analysis of the accuracy generated from the method produced by a combination of the Z-score and Min-Max Normalization methods, and is carried out Cluster homogeneity test using the Silhouette Coefficient method. The results of this method show that the Canberra method is superior to Euclidean and Manhattan on Iris dataset and the Canberra combination method with Z-score and Min-Max can increase the value on the glass without using the Normalization Method 37. 44% to 67.46% use the Z-score and 56.52% use Min-Max and use an increase in the average value of the Silhouette Coefficient.

In this paper, we present our observation regarding the student's computational thinking skill in the region of Sumatera Utara, Indonesia. The observation is based on the result of Bebras Indonesia 2019, a computer-based countrywide test on computational thinking aimed at students in primary school, middle school, and high school. We collected the data in a specific targeted region (the province of Sumatera Utara), collects additional data from the participant's school, and analyse the data. Our objective is to find a pattern between the schools' approach, if any, regarding topics related to computation thinking to the ability of students to actually solve the problem based on their score in the test.

The current modern smartphones have been equipped with multiple sensors to add the functionality of the phones. Two of the most significant sensors, accelerometer and gyroscope, are intended to sense the movement and orientation of the phone. We performed research to evaluate the capability of these two sensors to detect a road's quality, which can be used to generate a map of road quality in a certain area. The research is done by placing the mobile phone in a flat area inside the car and ride the car through roads with various quality, especially the damaged ones. We collected the value of both sensors when passing through hollow, bumpy, and cracked roads with several variations of speed. Based on our test, we conclude that this method is not effective in detecting the quality of the road since it is hard to differentiate the data from other behaviours such as accelerating, braking, turning, or even the car vibration. In this paper, we present the method used to perform this research and the collected data that may help our conclusion.

We present a client-server based smartphone application that act as a music input device with several outputs. The application allows user to interact with one phone as the input and the server and hear the sound from several connected smartphones that act as clients. Since transmitting data may require some time, we need to deal with transmission delay. Hence, we developed an algorithm to detect the delay and synchronize these values between all connected devices. By agreeing to a single delay value, we were able to minimize the difference in playtime between server and connected clients. We performed the test by building an Android-based smartphone application, installing it to multiple devices, and connecting them to a WiFi-based local area network. The test shows that our proposed system has successfully reduce the difference between devices and the connected devices were able to produce sounds with insignificant delay.

In this paper, we propose a method to represent a new method to represent large-scale 3D terrain efficiently to be used in a client-server collaborative terrain editor. The objective is to design a terrain representation that allows changes to be distributed between connected clients without throttling the bandwidth. The method divides the terrain into smaller patches so it can be streamed partially to connected clients. Moreover, we also reduce the data representation by using 8-bit values and modify the terrain representation to decrease the inaccuracy caused by data reduction. We present a thorough description of the proposed method and a demonstration of the technique in a practical collaborative 3D terrain editor application. We performed several tests with different terrain specifications and measured the interactivity level of the application. Based on these tests, we can conclude that the proposed method is capable of reducing the time-to-interactive of the application and consequently increasing the interactivity level of the system.

Society as a collection of people who are connected together based on certain understanding and bind by the regulation is adapted to perform multiple functions that for the sake of engaging technology advancement to improve the quality of life. Thus, there are some opportunities for application development to cater to the needs in the complexity of interaction between the individual in the society, one of them is user group management. This study is aimed to design the business canvas and mobile application by integrating virtual communities based on national identity in the form of e-KTP through Scrum method. Therefore, there are some challenges should be considered in the process of identification such as the right resource to implement the smart platform and the alignment between project objective and the readiness in the society. This study present APLICOT API as the framework for UGMS together with business model canvas, use case diagram and prototype.

Automatic Speech Recognition has penetrated deeply into our life. For well-resourced language, it can be considered as solved, but that's not the case for under-resourced language like Bahasa. Although it's the 7th most spoken language in the world, the research of speech recognition for Bahasa was still extremely limited, with setting still inconvenient for the real world and industry. This research is an attempt to make a speech recognition model that has applicability to the real world and industry, specifically that supports sentence level input with variable character length with end-to-end training. We built the model using the deep learning approach, specifically utilizing the residual networks and Bi-Directional Gated Recurrent Unit (Bi-GRU). To the best of our knowledge, this is the first Indonesian ASR model that can be trained in an end-to-end manner. Our model surpassed the baseline model on all metrics and achieve competitiveness with the current best result, which used the visual modal, for the dataset even with a more difficult and prone to noise modality like sound.

An essay test is the type of test that requires students' skills to propose, arrange, and combine the ideas they have from the teaching-learning process conducted. The essay answers in the form of description cause the examination becomes more complicated compared to an objective multiple-choice test. Therefore, in this research, the scoring system is built for an essay test by Using Latent Semantic Analysis that can pay attention to the word synonym of the key answer on the students' answer. The highest accuracy from the test that had been conducted at the essay scoring system by Using Latent Semantic Analysis was 84.35%, categorized into good.

Inserting data into digital media tends to change the large size of the media cover file, this is because the inserted pixel has a different size from the insertion value, i.e. with a larger or smaller value, for example a pixel value of 10 is inserted with larger or smaller data from the value 10. So that the pixel value is getting further from the value of 10, this causes the value of Mean Squared Error (MSE) of the media of the cover (cover) to become larger. In this study, the selection of pixels in the image is in accordance with the value of the insertion data as the insertion place with the Genetic algorithm (GA). Insertion of data on selected pixels using the GA algorithm is performed using the Modified Least Significant Bit (MLSB) algorithm at the position of the least significant bits. To find out the reliability of the proposed algorithm, the data insertion experiment was carried out by comparing the conventional LSB algorithm with the proposed algorithm where the results obtained a significant MSE value, i.e. the average MSE value of the LSB algorithm was 20.54 and the proposed algorithm was 7.12.

Classification is an important technique in data mining to create patterns and data modeling. Hepatitis is a disease that is dangerous to humans as this disease affects the human liver which is a vital organ. Early detection of hepatitis by diagnosing its occurrence on patients is needed to give them help, care, and treatment. Therefore, a classification technique is required to create patterns and models of data. To achieve accuracy in classifying hepatitis there would be requirements to separate relevant from irrelevant features. By only considering relevance features in classifying hepatitis, it is expected that the classification process will be faster, easier, and more accurate. In this research, the ANFIS algorithm and genetic algorithm are used in classifying the diagnosis of hepatitis based on a dataset from the UCI data mining repository. Results obtained showed that the genetic algorithm gave a slightly higher accuracy of 98.73% compared to 86.67% results obtained using ANFIS.

Herbal plants are medicinal plants included in the first choice for medicinal ingredients for rural residents. Herbal plants such as ginger and lime are plants that are often used and have plants that are similar in level. One way to identify these types of plants is through stomata microscopic imagery. As for the inspection that is still done manually by the pharmacists, the manual inspection takes a long time and misidentification may occur because there are some similarities with direct viewing, so a method is needed to identify the types of herbal plants based on stomata microscopic images automatically and to improve accuracy in the identification process. The method proposed in this study is Probabilistic Neural Network for the identification of herbal plant types based on stomata microscopic images and the algorithm used to identify these plant types Probabilistic Neural Network (PNN). Before the identification stage, the image will go through three stages, namely preprocessing, segmentation and feature extraction using the Gray level co-occuration matrix method. After testing using 20 microscopic image data of ginger and bitter ginger stomata. It was concluded that the proposed method has the ability to identify types of herbal plants with an accuracy percentage of 90 %.

The use of the internet that is very high at this time in all fields requires continuous development to improve the quality of data transfer. By improving the quality of data transfer, all activities that use the internet for transactions can run well. Good data transfer is influenced by speed, while speed is influenced by strength. There are several things that affect the data transfer process, but this research only focuses on speed and signal. Neural Network algorithm is used to determine the optimal point of the signal, where the optimal signal point is the maximum data transfer rate. This algorithm can be used to determine the optimal point with an accuracy rate of 10%

Finance Technology (FinTech) is a combination of financial services and technology that ultimately changes the business model. Appears as changes in people's lifestyles are currently dominated by users of fast-paced information technology. Financial technology provider which includes payment systems, market support, investment management, and risk management, loans, financing, and capital providers, and other financial services. North Sumatra has 33 municipal districts with an area of 72,981.23 km2 and a population of 13,937,797 people, with a density of 191 people / km2. Each city district has various. Percentage of user demographics ranging from 0.07% to 66.9% spread in North Sumatera Province. This can be seen from each region having different interests and abilities. Each district has various merchants that are built on every corner or roadside sample of 1,300 user data. LRM method to transaction types is divided into two with a merchant transaction frequency value of 263 and transaction biller 448.

We present a simulation of the hydrogen gas production by steam methane reformer unit utilizing empty fruit bunch (EFB) of the oil palm tree by using Aspen Plus. The oil palm empty fruit bunches, as biomass, is one that can be used as an alternative energy source to generate power. This paper aims to determine the amount of hydrogen gas (H₂) can be obtained from five different EFBs samples, which are available as waste in the local area of Sumatera Utara Province. In the pyrolysis unit, the proximate and ultimate analysis of the EFB was introduced while developing the model in Aspen Plus simulation environment to get the syngas as a product from the pyrolysis process. The syngas out from the pyrolysis unit then going to a steam methane reformer unit to get hydrogen-rich gas. The results showed that, from five samples of EFBs, the H₂ obtained in the range of 0.90 kg/hr to 1.70 kg/hr.

Affinity Propagation Method it is necessary to modify the algorithm by using Principal Component Analysis (PCA). PCA method is used to reduce the attributes or characteristics that are less influential on the data so that the most influential attributes are obtained to then be carried out the clustering process with Affinity Propagation. The comparison results of the PCA + AP grouping model have better performance than the conventional AP grouping model. This is justified because the number of iterations and clusters produced by the PCA + AP clustering model does not change and converges when there are 8 optimal cluster clusters. While the performance of conventional clustering models produces an optimal number of clusters from 14 clusters with a significant number of iterations. So it can be concluded that the PCA + AP grouping model is suitable for the Air Quality dataset because it produces an optimal number of clusters and iterations of 8 clusters. The comparison results of the PCA + AP grouping model have better performance than the conventional AP grouping model. This is justified because the number of iterations and clusters produced by the PCA + AP clustering model does not change and converges when the optimal number of clusters is 5 clusters. While the performance of conventional clustering models produces a suboptimal number of 10 clusters with a significant number of iterations. So it can be concluded that the PCA + AP grouping model is suitable for the Water Quality Status dataset because it produces an optimal number of clusters and 5 cluster repetitions.

At present, the agricultural commodity marketing system in Indonesia is detrimental to farmers. Due to the low selling price due to its dependence on intermediaries. That dependency indicates the difficulty of farmers to obtain data or information related to the market. But now, the government has provided data on the commodity market for the public interest. This research seeks to provide alternative solutions by providing web-based decision support applications that can help farmers get optimum marketing in selling their commodities. The price and market location dataset and market conditions obtain by synchronizing data services for the Food Security & Counseling Agency (BKKP) in Yogyakarta. Application of decision models using AHP produces the best marketing decision recommendations in the form of market location and price, based on the location of the farmer's house and the condition of the commodity. System usability test results with 30 farmer respondents resulted in an average value of SUS 70.0, and SUPER-Q scored 79%. The application can be accepted by farmers to use.

Brain tumor is a condition in which abnormal cells grow unnaturally in the brain. Depending on the size and type, the abnormal cells called tumors can be life-threatening if the patient does not take immediate treatment. The cause of tumor growth in the brain is the presence of risk factors such as family history and ionization radiation. Patients with brain tumors will experience several symptoms of a headache, nausea, memory loss, and changes in vision, speech, and hearing. Detection of brain tumors can be performed with the help of the medical device of Magnetic Resonance Imaging (MRI) Scan. Through the image of MRI Scan results, radiology specialists will interpret and analyze the brain condition. However, analysis and conclusions for this matter take a long period of time. Therefore, a method is required to classify the brain tumors through MRI images automatically. The method used in this research is Counter-propagation Neural Network. Prior to classification, the brain's MRI image will be used as the input for the image pre-processing stage then go through the segmentation and feature extraction processes. Based on the test, it can be concluded that the proposed method can identify brain tumors with an accuracy of 92.5%.

Down Syndrome is a condition of the physical and mental underdevelopment of a child due to chromosomal development abnormalities. This condition has different facial symptoms. Although Down syndrome has a unique feature on the face, they have a similar face with their parents and siblings, so it is quite complex to tell the difference. These symptoms contain specific information for facial recognition. In this research, the proposed method consists of five stages. The first stage is the input image. The second stage is pre-processing which composed of grayscale and CLAHE processes. The third stage is the image segmentation to bring up the special features of the image. The process continued with feature extraction that will generate an invariant moment. The final stage is the classification process to determine the type of face such as mosaic, trisomy 21 or without syndrome. The test result using the test data of 22 images showed that the system has an accuracy rate of 91% with the success percentage for recall and precision is at 88%.

Leukocytes are blood cells that contain nuclei, also called white blood cells. Leukocytes have a role in the cellular and humoral defiance of organisms against foreign substances. Laboratory tests of blood samples greatly influence the diagnosis of a disease. Manual blood tests do have a low price but still have some weaknesses such as the length of time needed will be longer, because health practitioners must examine them carefully to avoid misinformation. To help overcome these weaknesses, a classification of types of infections was carried out based on the results of leukocyte examination. Classification is a grouping of data where the data used has a label or target class. So that the algorithms for solving classification problems are categorized into supervised learning. The purpose of supervised learning is that label data or targets play a role as a 'supervisor' or 'teacher' who oversees the learning process in achieving a certain level of accuracy or precision. The algorithm used in this study is K-Nearest Neighbour. The data used in this study as many as 2,098 results of complete blood tests taken from one hospital in Medan. This study resulted in a classification accuracy of 92%.

This study discusses effect of tournament selection on the way individuals compete on the performance of Genetic Algorithms so which one tournament selection is most suitable for the Traveling Salesman Problem (TSP). One algorithm in solving TSP is Genetic Algorithm, which has 3 (three) main operators, namely selection, crossover, and mutation. Selection is one of the main operators in the Genetic Algorithm, where select the best individuals who can survive (the shortest travel route). Tournament selection compares a number of individuals through a match to choose the best individual based on each fitness value, so that the winning individual (the individual going to the next generation) will be chosen. There is two way to compete in an individual in tournament selection is by tournament selection with replacement (TSWR) and without replacement (TSWOR). The final results of the study conducted TSWR gets the best fitness, even though the generation that gets the best fitness is reaching the maximum generation (takes longer to get the best fitness).

There are many infectious diseases still plaguing different nations of the world. Some of these infectious diseases such as HIV, malaria, Ebola, and Lassa fever tend to affect less developed nations including those in Africa. In order to combat these diseases, there is need for ready access to omics data as the knowledge gained from this data can be used to combat infectious diseases globally. This study proposes a Mobile Application Framework for the management of Omics Data and Knowledge Mining (MAFODKM). The proposed framework was designed using a layered architecture. A prototype client application was implemented using JavaScript. In order to make it cross-platform, Apache Cordova framework was leveraged. The proposed framework will among other benefits provide an integrated platform for researchers to collaborate and conduct omics-related research to fight infectious diseases.

This article has been retracted by the authors following an admission that this article is a duplicate publication [1].

IOP Publishing has investigated in line with the COPE guidelines, and agree that this article should be retracted.

The authors agree to this retraction.

[1] Simamora R. J, Girsang A.S, Jenson T 2019 Ant Algorithm Optimization for Clustering News Online, 2019 International Conference of Computer Science and Information Technology (ICoSNIKOM), pp 1-4

Retraction published: 24 May 2022