<![CDATA[CodeArtisan Auto Finance is a rural savings and loan institution whose creditworthiness assessment process is still performed manually through document verification, field surveys, and subjective evaluation. This process requires one to five days and increases the risk of human error. This study applies the Simple Additive Weighting (SAW) method within a Decision Support System (DSS) to improve the speed and accuracy of credit decision-making. The proposed system evaluates prospective customers based on ten criteria: collateral, loan term, domicile status, employment status, social obligations, relationship with savings products, loan amount, expenditure-to-income ratio, planned installment-to-income ratio, and credit history. Evaluation on 37 historical customer records achieved an accuracy of 81.08%, precision of 90.32%, and recall of 87.50%, demonstrating that the SAW method provides objective and consistent creditworthiness recommendations. Therefore, the implementation of the SAW method can support faster, more transparent, and reliable credit decision-making at CodeArtisan Auto Finance.]]>
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