Development of a Decision Support System for Motorcycle Credit Eligibility Using the TOPSIS Method - Endang Ayu Susilawati; Eva Novianti; Avida Awitia; Yahya (Journal TIFDA (Technology Information and Data Analytic), 2025)
The growing need for motorcycle financing in Indonesia has encouraged financial institutions to improve the accuracy and consistency of their credit evaluation processes. At PT FIFGROUP, the current assessment procedure still relies heavily on manual surveys and subjective judgments, which often leads to variations in decision outcomes and longer processing times. This study aims to design and develop a Decision Support System (DSS) that facilitates a more objective and efficient assessment of motorcycle credit eligibility by applying the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Recent advancements in decision-making research highlight TOPSIS as one of the most effective multi-criteria decision-making (MCDM) methods due to its structured approach in comparing alternatives against ideal benchmarks. Building on this body of work, the proposed system incorporates organizational criteria—such as residential status, income stability, expenditure levels, and educational background—into a standardized evaluation model.The research methodology includes system requirement analysis, conceptual and database design, and the integration of the TOPSIS algorithm into the application workflow. Through normalization, weighting, and distance calculations, the system generates a final ranking score that reflects each applicant’s eligibility. The results of the study show that the DSS significantly improves the consistency of credit evaluations, reduces subjective bias, and accelerates the decision-making process. Overall, the implementation of a TOPSIS-based DSS provides a practical and reliable solution for PT FIFGROUP to enhance the quality and efficiency of motorcycle credit assessments