Multi-Criteria Decision Support System for Web-Based Credit Approval: A Study of TOPSIS, MABAC, WASPAS, and MAUT Methods

The decision-making process in granting credit involves analyzing a series of alternatives using certain criteria.. The goal is to find the best alternative that meets these criteria. One method that can be used in the decision making process is Multi-Criteria Decision Making (MCDM) or Multi-Criteria Decision Analysis (MCDA). There are many MCDM or MCDA methods that can be used for decision making. This research aims to test the MCDM methods, namely TOPSIS, MABAC, WASPAS and MAUT in making decisions regarding credit acceptance. The dataset used in this research is data regarding credit acceptance with 5 criteria and 100 attributes. The method study was carried out by ranking all alternatives based on the best alternative and then comparing the ranking results of the four methods using Spearman and Kendall Tau rank correlations. And carry out sensitivity tests on the four methods to find the most sensitive method. The results of the comparison of the four methods show that there is a strong correlation between the MABAC and WASPAS methods. The sensitivity test results show that the TOPSIS method is the most sensitive method. Based on the correlation results, it can be concluded that the MABAC and WASPAS methods are the methods that produce the most similar rankings. Meanwhile, the most sensitive method is obtained by the TOPSIS method.