Model Multi Criteria Decision Making with Fuzzy ANP Method for Performance Measurement Small Medium Enterprise (SME)

SMEs have a very important role in the development of the economy in Indonesia. SMEs assist the government in terms of creating new jobs and can support household income. The number of SMEs in Madura and the number of measurement indicators in the SME mapping so that it requires a method.This research uses Fuzzy Analytic Network Process (FANP) method for performance measurement SME. The FANP method can handle data that contains uncertainty. There is consistency index in determining decisions. Performance measurement in this study is based on a perspective of the Balanced Scorecard. This research approach integrated internal business perspective, learning, and growth perspective and fuzzy Analytic Network Process (FANP). The results of this research areframework a priority weighting of assessment indicators SME.


Introduction
Currently, the number of SMEs in the city of Bangkalan Madura reached more than 125 thousand units. SMEs provide opportunities for economic growth, reduced unemployment, and poverty. It absorbs approximately 79.04 million workers or 99.4% of the total workforce (Bank Indonesia, 2006). SME productivity is also an important factor affecting the progress of SMEs, increasing the income of the community, and play a role in realizing national stability.There are many indicators or criteria in determining performance measurement and business strategic plan, so it takes a decision-making method many criteria. The method used in this research is Fuzzy Multi Criteria Decision Making (FMCDM). Fuzzy Method Multi-criteria is a method used to determine the criteria weighting of several alternatives based on one's assessment.
Fuzzy Multi Criteria Decision Making (FMCDM)method used in this research is Fuzzy Analytical Network Process (FANP). Analytic Network Process Method (ANP) is a method that can represent the importance of various parties by considering the interconnection between existing criteria and subcriteria [1] [2]. ANP is a development of AHP, has a more complex system of analysis and the consistency of index in the assessment of questioner [3]. Previous research has been done performance measurement according to indicator contained in balance Scorecard [3]. In this study more detail about the measurement of risk to SMEs. There are several performance assessment criteria: employee training, owner education, owner training, net income, sales transactions, ownership (shop), variations of batik motive, employee maturity, buyer satisfaction, preferred motives, raw material price 2 1234567890''"" increases, weather conditions, production. There are difficulties during qualitative performance measurements such as preferred motives, weather conditions, and others. In measuring qualitative factors using fuzzy numbers make decisions easier and get more realistic results [4].
This research, FANP method is used to determine the best criteria and decision-making based on the existing criteria, both qualitative and quantitative. The use of Fuzzy in this study to accommodate the vague nature of decision-making by giving consideration that can overcome the uncertainty in qualitative criteria [4] [5].

Fuzzy Theory
Fuzzy theory is used to overcome uncertainty due to imprecision and vagueness. Fuzzy contributed his ability to represent vague data [6]. The set is marked by a membership function (characteristic), which assigns each object a membership value ranging between zero and one [7].  (u ) / (u );

Fuzzy Analytical Network Process (FANP)
Fuzzy ANP method is applied for an extension of the AHP and ANP by combining the fuzzy set theory. In the ANP Fuzzy, Fuzzy ratio scale used to indicate the relative strength of the factors on which the relevant criteria. The fuzzy decision so that a matrix can be formed. Kahit of alternatives are also presented in the Figures Fuzzy [8]. Based Chang each object of each criterion and sub-criteria to be considered and extend the analysis to obtain a goal executed. This means it is possible to obtain the analysis which can extend the value indicated by the notation as follows [9]. ...
To get this Framework model for measurement of the SME is provided in Fig. 2.3.

Results and Analysis
This stage consists of modeling, simulation, and analysis of results. The modeling stage is theidentification of MCDM problems by determining the number of variables to be used in the study (criteria, alternatives, and respondents) as shown in integrated internal business perspective, learning and growth perspective [11]. The next stage is Simulation and Analysis. Based on the framework model, the simulation and analysis of the model have been made based on existing indicators in SME. This is done to determine the optimal solution in decision-making and the smallest threshold value to determine the recommendation of Strategy map SME, SWOT, and clustering SME.
The stages of the simulation of this research program is     method determines the weighting of criteria based on the level of importance of the SME. This framework is adaptive and dynamic. The advantages of this Framework is to provide benefits for decision makers in determining the fuzzy scale and iterating dynamically to get the optimal decision. The resulting decisions can have high accuracy if there are preliminary data. Decisions are taken also consider the opinions of respondents by checking the consistency ratio. Future research on SME measurements can be used Adaptive Interval Fuzzy AHP and Adaptive Interval Fuzzy ANP.