The prioritization of loan rescheduling for non-performing debtors with collectability scores above 3.00 is often inaccurate, as it typically relies on a limited set of evaluation criteria. These debtors, categorized as non-productive, contribute to the deterioration of financial institution performance. In practice, misaligned restructuring decisions frequently occur because the evaluation process does not incorporate assessments from multiple relevant parties. This condition creates significant challenges in producing objective and consistent decisions.To address this issue, a Group Decision Support System (GDSS) is proposed for KSP Makmur Inti Sentosa. The system integrates the Analytical Hierarchy Process (AHP) for determining criteria weights, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking alternatives, and the weighted Borda method to incorporate decision-makers’ preferences. By combining these methods, the GDSS is expected to improve the accuracy, objectivity, and efficiency of decision-making in prioritizing credit restructuring for problematic debtors.The assessment using a combination of the AHP-TOPSIS and weighted BORDA methods generates a hybrid score in which BORDA voting contributes 30% to the final evaluation, thereby producing recommendations that place greater emphasis on the qualitative values of the customers.
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Universitas Gadjah Mada
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