The Road’s Level of Service at Kawi Road, Malang Regency

A region’s ability to expand and flourish depends heavily on its road system. Roads that are smooth and effective facilitate communication between different locations, the movement of people, and the transit of commodities. Thus, people movement within a region is greatly impacted by the quality of road service. One of the principal thoroughfares in Malang Regency is Kawi Road, which has two two-way lanes without a median and an effective road width of eight meters. It is a primary collector hierarchy (2/2 UD). There is a lot of traffic on Kawi Road since it connects two local activity hubs, Blitar and Lumajang, and acts as a national road. This study’s main objective is to characterize Kawi Road in Kepanjen District, Malang Regency, with regard to its attractiveness and generation of land use, performance, and modeling. In compliance with the 2014 Indonesian Road Capacity Guidelines, the following research methodologies were used: road capacity analysis, saturation degree analysis, multiple linear regression analysis, and road service level analysis. The research makes use of field observation data. According to calculations, Kawi Road can handle 2826.63 passenger car units per hour. Its peak performance was reached between 15:00 and 16:00, or 0.87 (LOS E).


Introduction
Given that it acts as a catalyst, a driving force, and a cohesive factor in bridging regional differences, transportation is one of the factors that should be taken into account in regional development planning [1].A structured system that includes flow methods, regulatory frameworks, and infrastructure specifically designed to facilitate the rapid, efficient movement of people and products between locations in order to support human activities is called transportation [2].It is impossible to overestimate the critical role that transportation plays in promoting the social and economic development of communities [3].Access to jobs, housing, services, and recreational opportunities is made possible by transportation, which also helps to reveal the potential of remote and rural areas [4].Over time, human activities become more diverse, which propels transportation technology forward [5].
Infrastructure plays a crucial role in development initiatives.Sufficient infrastructure facilitates the achievement of development objectives in a specific area [6].An essential first step in enabling economic and mobility pathways is infrastructure [7].Restricted infrastructure development, particularly in the area of roads, can lead to limitations and a slow rate of investment in a region [8].A city's expansion can be impacted by its growing populace and activities.The complexity of urban life and growing population combine to drive up demand for transportation infrastructure, particularly 2 highways [9].When road capacity is exceeded by traffic volume, land use control is required [10].A geographical area is shaped in part by the interdependence of transportation and land use systems.Land use planning should ideally serve as the foundation for efforts to provide transportation facilities for regional development [11].
Transportation-related activities rise together with a region's economic and demographic development.Ignorance of this can result in traffic issues, particularly the kind of congestion that Indonesian cities are currently experiencing.When demand and supply aren't balanced to maximize the number of vehicles within the capacity of the transportation infrastructure-which includes public transportation and road networks-traffic congestion is typically the result [12].
The formal relocation of the capital of Malang Regency from the City of Malang to the Kepanjen Subdistrict is marked by the adoption of Government Regulation No. 18 of 2008 on the Relocation of the Malang Regency Capital from the City of Malang to the Kepanjen Subdistrict of Malang Regency.One of the most populated subdistricts in Malang Regency is the Kepanjen Subdistrict, which serves as the capital.The population density of 2,403 persons/km² in Kepanjen Subdistrict is the third highest in Malang Regency according to Central Bureau of Statistics Malang Regency.Furthermore, according to the Malang Regency 2010-2030 Spatial Plan, Kepanjen Subdistrict is the hub of regional activities including trade, services, healthcare, places of worship, offices operating at the regional and national levels, and sports and artistic endeavors.As a result, the population mobilizes every day to satisfy their demand for activity.The Kepanjen Subdistrict's main roadways, particularly the Kawi Road Corridor, see an increase in traffic density as a result of the growing population and improved mobility.
Kawi Road, which runs from Kepanjen to Blitar, is an east-west route that crosses a variety of land uses and may occasionally cause severe traffic congestion.Along Kawi Road, there are also street vendors (PKL) that set up shop along the side of the road.The Kawi Road segment's road service level was assessed as D in 2020 according to the Transportation Agency of Malang City's estimations of road performance.If changes in land use activities along Kawi Road result in an increase in the number of vehicles being driven, this circumstance may become problematic.Therefore, more research is required to evaluate the effectiveness of this road corridor in reducing traffic congestion and its causes as well as to offer exact guidelines for maximizing vehicle comfort and ease of movement.

Methods
This work uses a quantitative approach to descriptive research, emphasizing the measurement of variables in relation to each other and the statistical support of these measurements.The descriptive research in the framework of this study aims to give a summary and characterize factors pertaining to the influence of land utilization on the quality of road service along the Jalan Kawi Corridor.
The data collection methodologies utilized in this study comprise primary surveys that involve field observations, interviews, and questionnaire administration; secondary surveys include an extensive review of relevant literature, agency surveys, and comparative studies.Regarding analytical techniques, the research employs a broad strategy that includes descriptive analysis to investigate road and land use characteristics, correlation analysis to identify associations, multiple linear regression to perform predictive modeling, analysis of road capacity, and a service level assessment.Figure 1 presents the procedural aspects of these analyses visually.

Data Collection Technique
Data gathering techniques employed both primary and secondary surveys, Field observations, interviews, and questionnaires were used in the main survey.Land usage, road geometry, traffic enumeration, and plate matching are among the needs assessed [13].A geometry survey and a traffic enumeration survey were the two parts of the observation study [14].By monitoring, measuring, and recording Kawi Road, the road geometry survey assisted in determining the capacity and characteristics of the road.Vehicles traveling down this road were counted and categorized as part of the traffic enumeration survey [15].Along the Kawi Road corridor, observations were made at both ends of the road and in front of residential roads.Data was gathered from 06:00 to 21:00 over the course of two days, covering weekends and weekdays.
A secondary survey also included reading relevant literature, government publications, and earlier research.Documents include "Kepanjen District in Figures 2020," "Malang Regency Transportation Masterplan," "Spatial Plans Malang Regency 2010-2030," and "Detailed Spatial Plan Kepanjen District" were among the data sources.

Research Variables
The variables used in this investigation can help to address the goals of the study.The variables used in this study are as follows: Table 1.Research Variables Variables in Table 1 Several sources of research on the interaction of land use with road performance have been carried out.In each aspect, there are variables Y and X.

Population and Sample
Stratified random sampling is the basis for the sample strategy used in this investigation.The method described by Isaac and Michael is used to determine the sample size, and a predetermined margin of error of 5% is used [18].The following formula is used to determine the sample size using the Isaac and Michael method [19]: Based on the current land uses, the population on Kawi Road is represented by the statistics in Table 2. On this road, samples of the land use and population units were collected.A sample of the entire population was taken, and the sample size was established.This land use sample is used for internal volume estimation, land use creation, and attraction.

Methods of Analysis 2.4.1 Road Capacity Analysis
According to the Indonesian Road Capacity Guidelines, capacity is the highest traffic volume that can be sustained per hour at a given location on a toll-free road under the current circumstances [20].The formula for road capacity is as follows [21]:

Correlation Analysis
One statistical method for figuring out how much a variable and another have a linear association is correlation analysis [22].The following formula is applied: (3) r pearson's correlation correlation X Independent variable Y Dependent variable

Multiple Linear Regression Analysis
The goal of multiple linear regression analysis is to evaluate the strength of the associations between two or more variables and produce estimates or forecasts for the values of Y and X [23].The following formula is applied:

Road Network -Land Use Interaction Model
The interaction model is employed to determine the relationship between land use systems and network infrastructure by using different functional methods and formulas.Equation provides the following details in detail [24].

Road Level of Service
Route performance is assessed by measuring the degree of saturation, which represents the ratio of traffic to capacity on the route [25].One of the main factors affecting how well intersections and road segments function is this ratio [26].The degree of saturation formula is:

Characteristics of the Road Network
The Kawi Road Corridor has an asphalt pavement and is categorized as a 2/2 TT road type.Kawi Road has an effective road width of eight meters and functions as a key collection road.The Kawi Road Corridor has multiple locations set aside for on-street parking and street vendors (PKL).The numbers obtained for the Kawi Road are: C0 = 2900; FCLJ = 1.14;FCPA; FCHS = 0.95; FCUK = 0.9.Consequently, Kawi Street's computed capacity is found to be 2826.63pcu/hour..

Characteristics of the Land Use
There are 101 land uses overall along the Kawi Street Corridor, divided into 5 categories.These consist of fourteen housing units, sixty-two trade and service units, one minimarket unit, two healthcare units, eighteen office units, and four educational units.With 61% of all land uses present, trade and services are the most prevalent land uses along the Kawi Road Corridor.

Characteristics and Movement Generation / Attraction Land Use
The number of vehicles entering and leaving a land use is given in terms of pcu/hour to represent the movement of origin and destination.Depending on the kind of land use, the features of the origin and destination movements along Kawi Street are explained.The changes in land use on Kawi Street are as follows: • Housing: 49.

Modelling Land Use in Region Research
Multiple linear regression and correlation analysis were used to create the land use generation and attractiveness models.The generation-attraction models for each land use are as follows: • Housing: The land use generation model for housing is YHousing = -0.173+ 0.824(X1) + 0.403(X2), where X1 represents the independent variable of the number of household members (people) and X2 represents the independent variable of motor vehicle ownership (units).• Trade and services: The land use attraction model for trade and services is YTrade and services = 0.739 + 0.482(X7) + 0.015(X8) -0.005(X9),where X7 represents the independent variable of the number of visitors (people), X8 represents the independent variable of building area (m 2 ), and X9 represents the independent variable of parking area (m 2 ).• Minimarket: The land use attraction model for minimarkets is YMinimarket = -0.363+ 0.352(X11) + 0.063(X13), where X11 represents the independent variable of the number of visitors (people) and X13 represents the independent variable of parking area (m 2 ).• Healthcare: The land use attraction model for healthcare is YHealthcare = 0.840 + 0.327(X22) + 0.111(X23), where X22 represents the independent variable of the number of visitors (people) and X23 represents the independent variable of building area (m 2 ).• Offices: The land use attraction model for offices is YOffices = 5.989 + 0.401(X30) + 0.333(X31) + 0.025(X32), where X30 represents the independent variable of the number of employees (people), X31 represents the independent variable of the number of visitors (people), and X32 represents the independent variable of building area (m 2 ).• Education: The land use attraction model for education is YEducation = 6.417 + 0.116(X34) + 0.022(X37), where X34 represents the independent variable of the number of students (people), and X37 represents the independent variable of parking area (m 2 ).

Volume Vehicle Movement 3.5.1 External Volume Vehicle Movement
The external vehicle movement is the continuous movement of vehicles on the Kawi Street Corridor, as indicated in Tables 3 and 4 below.

Internal Volume Vehicle Movement
The data on origin and destination movements inside the land uses along the corridor is used to calculate the internal volume of vehicle movement.It is concluded that the Kawi Road corridor displays variable service levels at different hours based on Table 8 and Figure 2.With a LOS (Level of Service) rating of F, the poorest level of service is seen between 13:01 and 14:00.The creation of vehicle movements related to land access has a considerable impact on road service performance, as determined by the study's findings.These results are consistent with another research, who looked at how the Tanah Merah Market Activities Affected the Tanah Merah Highway Segment's Performance in Bangkalan District [27].Traffic volume, which accounted for 79% of the overall volume at 13,990 vehicles per hour, was shown to have the greatest significant influence in Inayah's study.The volume of land used had an 18% influence; of all the land uses, Tanah Merah Market land use had the most impact, accounting for 65%.

Conclusion
Using the following calculations, it can be shown that the actual capacity on the Kawi Street Corridor was 2826.63 pcu/hour: C0 = 2900; FCLJ = 1.14;FCPA; FCHS = 0.95; FCUK = 0.9.There are 101 land uses altogether along the Kawi Street Corridor, divided into 6 categories.These categories consist of 14 residential units, 62 trade and service units, 1 minimarket unit, 2 healthcare units, 18 office units, and 4 educational units.With 61% of all land uses present, trade and services are the most prevalent land uses along the Kawi Road Corridor.Furthermore, the study aims to create a relationship between the total number of vehicle movements per hour along the Kawi Street Corridor and the capacity of the road in order to assess the quality of service provided by the road.The influence of land use on the volume of vehicle movements, which in turn affects the road's level of service, highlights the relationship between land use and the road's level of service within the context of the road network.The computations show that the Kawi Road corridor has variable service levels at different times of the day.With a LOS (Level of Service) rating of F, the poorest level of service is seen between 13:01 and 14:00.

Figure 1 .
Figure 1.Method Framework of employees X19 = Number of visitors X20 = Building area X21 = Parking area The attraction of land use for education YSchool X22 = Number of students X23 = Number of teachers/employees X24 = Number of classrooms X25 = Parking area X26 = Building area Interaction of land use and road

Table 2 .
Population and Sample used in study 80 pcu/hour is the overall movement of housing land use on Kawi Street.The highest origin and destination movement, with a ratio of 15.06% and 7.50 pcu/hour, takes place between 06:01 and 07:07.• Trade and services: Kawi Street's overall land use movement for trade and services is 22.80 pcu/h.The highest destination movement, 3.75 pcu/hour and 16.45% ratio, happens between 16:01 and 17:00.• Minimarket: On Kawi Street, the overall movement of minimarket land use is 71.30pcu/hour.Between 14:01 and 15:00, there is the greatest mobility of origin and destination, with 8.45 pcu/hour and an 11.85% ratio.• Healthcare: On Kawi Street, the overall movement of land used for healthcare is 20.80 pcu/hour.Between 08:01 and 09:00, there is the greatest mobility of origin and destination, with 3.40 pcu/hour and a ratio of 16.35%.• Offices: 32.60 pcu/hour is the overall movement of office land usage on Kawi Street.Between 09:01 and 10:00, there is the greatest mobility of origin and destination, with 8.95 pcu/hour and a ratio of 27.45%.• Education: On Kawi Street, the total movement of land used for education is 70.10 pcu/hour.The maximum movement of origin and destination, with a ratio of 31.17% and 21.85 pcu/hour, happens between 06:01 and 07:07.

Table 3 .
Continuous Movement Volume on the Corridor of Kawi Street (Weekdays)

Table 5 .
Volume vehicles movement from land use on the Corridor of Kawi Street Table5indicates that, with a total of 4.9 pcu/hour, the lowest volume generation/attraction of vehicle movement based on land use on the Kawi Street Corridor occurs between 19.0 and 10.00.At the same time, the largest volume of 40.85 pcu/hour occurred between 15.01 and 16.00.3.5.3 Alleyway Volume Vehicle MovementAccording to Table6, local roads near Kawi Road, in particular Punten Road, contribute 51.35 pcu each day on weekdays.At a rate of 18.40 pcu/hour, the peak total volume happens between 12:00 and 13:00 hours.Conversely, the lowest total volume, which happens between 06:00 and 07:00, is -5.65 pcu/hour.

Table 8 .
Model of Interaction of Land Use and Road's Level of Services Figure 2. Graphic of Model of Interaction of Land Use and Road's Level of Services