Sistem Penunjang Keputusan Menentukan Senjata Terbaik pada Komunitas VIC Menggunakan Perbandingan Metode SAW dan WP

Abstract

Weapon selection in Valorant has generally been based on subjective judgment, resulting in inconsistent and less objective decision-making. This study aims to develop a Decision Support System (DSS) to assist players in selecting the most suitable weapon based on objective criteria, including damage, range damage, recoil, fire rate, and magazine capacity. The system is designed to identify the optimal weapon according to players' needs while evaluating the effectiveness of the Simple Additive Weighting (SAW) and Weighted Product (WP) methods. The system was developed using the Waterfall software development model, which consists of requirements analysis, system design, implementation, and testing. The dataset comprises 18 Valorant weapons evaluated using five assessment criteria. The ranking results generated by the SAW and WP methods are relatively consistent, with the highest-ranked weapon recommended as the optimal choice. Furthermore, the Spearman Rank Correlation test produced a coefficient of ρ = 0.75, indicating a strong positive correlation between the two methods. The results demonstrate that the proposed Decision Support System is capable of providing objective, structured, and more accurate weapon recommendations than conventional manual selection methods, thereby supporting more consistent decision-making and gameplay strategies for Valorant players and the Valorant Indonesia Community (VIC).