IMPLEMENTASI HYBRID AHP-TOPSIS PADA SISTEM PENDUKUNG KEPUTUSAN EVALUASI PERFORMA PRAMUDI - Pratiwi Cahyaningtiyas; Rhoedy Setiawan; Soni Adiyono (Rabit : Jurnal Teknologi dan Sistem Informasi Univrab, 2026)
Subjective bias, delayed data accumulation, and unfair bonus allocation are common issues resulting from the manual pramudi appraisal method at PT Samudra Jaya Transport. To resolve these challenges, this research develops a web-based Decision Support System (DSS) integrating the Analytical Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The AHP method is employed to establish priority weights for five core criteria: cargo, attendance, discipline, fuel consumption, and fleet maintenance. Concurrently, TOPSIS is implemented to rank 107 pramudi partitioned into three distinct categories: New Pramudi, Senior Pramudi, and Experienced Pramudi. The AHP evaluation yields a reliable Consistency Ratio (CR) of 0.0259. Furthermore, the TOPSIS analysis identifies the leading preference scores for each cluster, specifically PB-01 at 0.7909, PS-01 at 0.8691, and PSE-01 at 0.9308. Black-Box testing confirms that all core system features function correctly. Ultimately, this system ensures a data-centric evaluation process, eliminates bias, and delivers highly transparent monthly bonus recommendations.