CREDIT ACCEPTANCE DECISION SUPPORT SYSTEM, A COMPARISON OF SAW, TOPSIS, AND SAW–TOPSIS METHODS - I Putu Eka Sudarsana (Institute of Computer Science (IOCS), 2022)
This study aims to compare the three methods of Decision Support Systems in assessing/recommending the provision of business credit at the Karya Sejahtera Cooperative. The three methods are: Simple Additive Weighting (SAW), Technique for Order by Similarity to Ideal Solution (TOPSIS), and a combination of the SAW and TOPSIS methods using five criteria, namely: Guarantee, Income, Loan Application Form, Business Establishment Permit, Land Building Tax. In addition to comparing methods, method testing was also carried out. It aims to find the most appropriate/relevant method in conducting the assessment. The test method uses the mean average precision technique which tests the accuracy of the debtor ranking. The comparison between the SAW, TOPSIS, and SAW-TOPSIS methods was tested using the mean average precision technique which shows that based on the test results of each method, the SAW - TOPSIS method is the method with the best accuracy when using the top 10 data rankings with a value of 83.7%. With a MAP test rating of 66%, the TOPSIS technique is the method with the second best accuracy when using the top 10 ranking data. In testing utilizing the MAP methodology, the SAW method had the third best accuracy when using the top 10 ranking data, with a value of 54.3%. The MAP test findings suggest that future research methods can include many methods for comparing outcomes, and the results of the calculation analysis can be further developed by adding data and being evaluated using other testing procedures to obtain different results.