<![CDATA[The credit granting process in savings and loan cooperatives often faces obstacles in terms of objectivity and efficiency of assessment of prospective debtors. Manual and subjective assessments have the potential to result in inaccurate decisions and increase the risk of problematic credit. This study aims to develop a Decision Support System (DSS) in credit granting by implementing the Simple Additive Weighting (SAW) algorithm combined with the Entropy weighting method. The SAW method was chosen because of its ability to calculate aggregate values against a number of criteria, while the Entropy method is used to determine the weight of the criteria objectively based on data variations. The criteria used include monthly income, credit history, number of dependents, length of membership, and history of installment ratio to income. The results of the study showed that the system was able to systematically sort 15 alternative customers. Based on the final calculation results, the customer who obtained the highest score of 0.862 and was ranked first as the best candidate for credit recipients. These results indicate that the SAW method with Entropy weighting can provide objective recommendations and help make more appropriate decisions in granting credit. The main contribution of this research is to provide a technology-based tool that can improve accuracy, transparency, and efficiency in the creditworthiness evaluation process in savings and loan cooperatives.]]>
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