Web-Based Decision Support System for Paskibra Member Selection Using the Fuzzy Sugeno Method

Abstract

This study designed and built a web-based Decision Support System (DSS) that applied the Fuzzy Sugeno method to support Paskibra member selection at the district level, where manual scoring had left qualitative criteria such as the interview without a firm boundary between eligibility categories. Three criteria were used: Height, Knowledge Test Score, and Interview Score. Sugeno was selected because its rule consequents were crisp values, which allowed a lightweight weighted-average defuzzification instead of the heavier defuzzification required by Mamdani. The system was built with PHP, MySQL, and Bootstrap, converting each criterion into fuzzy membership degrees and evaluating a configurable IF-THEN rule base to produce a final score. Testing combined Black Box Testing across ten functional modules and White Box Testing with cyclomatic complexity analysis on the core calculation module. The Black Box results showed all modules functioned as intended, while the White Box analysis yielded a cyclomatic complexity of V(G) = 3, with all three independent paths executing without logical error. The resulting system offered selection committees a traceable, rule-based alternative to manual scoring, in which criteria weighting could be adjusted through the rule base rather than through code changes.