A Fuzzy Tahani-Based Decision Support System for Selecting Academic Achievement Scholarship Recipients
TL;DR
This modified Fuzzy Tahani framework offers a reliable and validated multi-criteria decision-making system that other higher education institutions can adapt to ensure more equitable scholarship allocations.
Abstract
Scholarship programs are essential for increasing access to higher education, yet selection processes are frequently hindered by subjective reasoning and procedural inefficiencies. This study presents an advanced Decision Support System (DSS) for academic achievement scholarships at Universitas Islam Majapahit using a modified Fuzzy Tahani method characterized by a dual-platform architecture, socio-economically tailored membership functions, and complete operational transparency. The model evaluates four primary criteria—Grade Point Average (GPA), parental income, number of dependents, and non-academic achievements—to provide objective prioritization through fuzzification and defuzzification processes. Testing conducted on 18 applicants across Microsoft Excel and Android platforms demonstrated 100% computational accuracy and a Spearman’s rank correlation of 1.0, confirming identical ranking consistency. Furthermore, the system exhibited high efficiency with processing times of 35 seconds on Excel and 2 seconds on Android, while sensitivity analysis and a 94% expert validation rate underscored its procedural robustness. The results indicate that students possessing high academic merit alongside significant financial need were consistently prioritized, addressing previous systemic deficiencies in fairness and transparency. Ultimately, this modified Fuzzy Tahani framework offers a reliable and validated multi-criteria decision-making system that other higher education institutions can adapt to ensure more equitable scholarship allocations.