Futsal's popularity remains undiminished, captivating communities, including school environments like SMK Unitomo Surabaya. In this school, building a strong futsal team is the cornerstone of achieving success. However, manual player selection processes often encounter obstacles, such as inefficiency and potential subjectivity. Often, coaches do not record selection results, leading them to evaluate selections subjectively.Therefore, this research presents a solution in the form of a Decision Support System (DSS) to assist coaches in identifying potential core futsal players. This DSS integrates two cutting-edge methods: Rank Order Centroid (ROC) and Additive Ratio Assessment (ARAS). The ROC method plays a role in data weighting, assigning measurable values to each selection criterion. On the other hand, ARAS plays a role in determining the best alternative by comparing the overall value of each alternative with the optimal value of the entire series. Research results demonstrate that this DSS can generate rankings of potential core futsal players with an accuracy level of 0.8753324. This indicates that this DSS has great potential to assist coaches in selecting the right players and increasing the team's chances of winning.
Copyrights © 2024