Min-Max Fuzzy TOPSIS with Entropy Weighting for Strategic Location Multicriteria Decision Making - Endah Nurfebriyanti; Parapat Gultom; Tulus Tulus (ZERO: Jurnal Sains, Matematika dan Terapan, 2025)
This study aimed to develop a robust, objective framework for strategic location Multicriteria Decision Making (MCDM) by effectively addressing criteria conflict and data uncertainty. The research methodology utilized a novel hybrid approach, integrating the Entropy method to determine objective criteria weights with a Min-Max Fuzzy TOPSIS model, a modification adopted specifically to improve the consistency and rationality of alternative ranking results. The model was applied to a case study concerning strategic location selection in Batubara Regency, evaluating five alternative locations based on six criteria. The major finding from the objective weighting process was that the Number of Students ( ) was the most influential criterion, receiving the highest weight of 0.294. Subsequent analysis using the modified Fuzzy TOPSIS revealed that Alternative (Madang Deras) achieved the highest performance index , securing the first rank. Numerical validation showed a significant improvement over existing approaches. When compared with the original Min-Max Fuzzy TOPSIS, the Performance Index of the best alternative ( ) increased from 0.588 to 0.673, representing a 14.46% improvement. Furthermore, when evaluated against a model using uniform weighting, the Performance Index increased from 0.449 to 0.673, reflecting a substantial 49.89% enhancement. These results demonstrate that entropy-based objective weighting meaningfully improves the discriminative power of the decision model and reduces bias. Overall, the proposed hybrid framework offers a more stable, accurate, and comprehensive approach for strategic location selection.