Sistem Pendukung Keputusan Pencarian Bakat Pemain E-Sport Mobile Legends menggunakan Metode Moora Berbasis Web

Abstract

Along with the rapid growth of the e-sports industry, particularly in the game Mobile Legends: Bang Bang, significant opportunities have emerged for young players to pursue professional careers. However, in e-sports communities such as Sharing Gils Blog, the talent scouting process is still conducted subjectively without the support of a structured and data-driven system. This study aims to develop a web-based Decision Support System (DSS) as a tool to assist the e-sports player selection process so that it can be carried out objectively, efficiently, and accurately. The MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) method is applied as a multi-criteria decision-making technique due to its ability to process various evaluation criteria that have been weighted according to their respective levels of importance. The criteria used include both mechanical and non-mechanical aspects relevant to player performance, such as in-game statistics, strategic ability, team communication, and performance consistency. The research stages consist of data collection through interviews, observations, and literature studies, followed by system requirements analysis, determination of evaluation criteria, system design and development using the Rapid Application Development (RAD) approach, and system testing using black box and white box methods. With appropriately assigned weights, the system is able to perform objective calculations and generate measurable recommendations for selecting the best players. The testing results indicate that the system operates as expected and is capable of supporting a more transparent and fair decision-making process in the selection of talented players within e-sports communities.