Dynamic Value for Money Index-Based Hybrid Fuzzy AHP-TOPSIS for Used Vehicle Recommendation Considering Market Depreciation and Maintenance Cost

The rapid growth of Indonesia's used car market, driven by the high price and fast depreciation of new vehicles, has increased the risk of information asymmetry between buyers and sellers in determining a fair value-for-money price. This study developed a website-based decision support system for used car selection that integrates the Fuzzy Analytic Hierarchy Process (FAHP) for criterion weighting with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for alternative ranking. Eight criteria, comprising document completeness, odometer reading, spare parts availability, service record, interior condition, exterior condition, assembly year, and price, were weighted through pairwise comparisons with a used car showroom owner and applied to rank five used car alternatives. The Fuzzy AHP weighting produced consistent criterion weights, with document completeness and odometer reading identified as most influential. The TOPSIS ranking identified a 2023 Toyota Innova Zenix as the recommended alternative despite its higher price, owing to its newer assembly year, lower mileage, and better overall condition. Comparison between the manual calculation and the system output showed an identical ranking order, confirming correct implementation. This study demonstrates that integrating Fuzzy AHP and TOPSIS can support more objective and transparent used car purchasing decisions.