An AHP–TOPSIS-Based Decision Support System for Objective Pencak Silat Athlete Selection at KONI Lamongan

Ahmat Rendi Saputra
Brina Miftahurrohmah (Semen Indonesia International University (UISI))

JISA (Jurnal Informatika dan Sains)
Vol 9, No 1 (2026): JISA(Jurnal Informatika dan Sains)

Sports achievement development requires an objective and measurable athlete selection mechanism, particularly in regional sports organizations preparing for competitive events. However, the athlete selection process conducted by Komite Olahraga Nasional Indonesia (KONI) Kabupaten Lamongan for the Pencak Silat branch in preparation for PORPROV Jawa Timur IX 2025 still relied on conventional weighting based on subjective estimation, namely 40% physical test and 60% achievement certificate assessment. This mechanism potentially generated decision bias, especially in evaluating athlete candidates with diverse physical capabilities and competition backgrounds. Therefore, this study aimed to develop a Decision Support System (DSS) using the integration of Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods to improve the objectivity and consistency of athlete selection. The study involved 26 athlete candidates evaluated using nine physical performance criteria and seven expert respondents consisting of KONI management representatives, coaches, and Monitoring and Evaluation (MONEV) personnel. The AHP method was applied to determine criterion weights through pairwise comparison and consistency testing, while TOPSIS was utilized to rank athlete candidates based on their proximity to ideal solutions. The results showed that Sprint 30m, Illinois Agility, Stork Stand, Standing Board Jump, and Beep Test obtained the highest priority weights of 14.94%. The consistency test produced a Consistency Ratio (CR) value of 0.0018, indicating reliable expert judgment consistency. Furthermore, the TOPSIS ranking process identified Sastro Hadi Saputro as the athlete with the highest preference value (Ci = 0.8954). The comparison between system-generated rankings and manual coach evaluations also demonstrated a high agreement level, with Spearman and Pearson correlation values of 0.9945 and 0.9863, respectively. These findings indicate that the integrated AHP–TOPSIS framework is capable of improving transparency, reducing subjectivity, and supporting more adaptive athlete selection decisions in regional sports organizations.