Nailul Hasan
Physics Study Program, Faculty of Engineering and Science, Pembangunan Nasional “Veteran” Jawa Timur University, Surabaya 60294, Indonesia

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Fuzzy Analytical Hierarchy Process Method to Determining Most Valuable Player (MVP) in E-Sport Nailul Hasan; Immanuel Siburian; Nenni Mona Aruan; Akbar Sujiwa
Nusantara Science and Technology Proceedings 5th International Conference Eco-Innovation in Science, Engineering, and Technology
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4505

Abstract

E-Sport is a type of sports field that uses electronic devices such as consoles, handphones, and computers in its matches. Nowadays, this field has even been competed as a World Cup. One of the most popular games of 2024 with 100 million views on the Twitch app is Valorant. This study aims to apply the Fuzzy Analytical Hierarchy Process (F-AHP) method in determining the best players in one of the Valorant tournaments. A case study for the Valorant Champions Tour 2021: Stage 3 Master-Berlin is presented in this study. Where in 9 criteria according to coach of the Korean E-Sport team recommendation as an expert are assessed: (1) First Kill per Round, (2) Kills per Round, (3) First Death per Round, (4) Clutch Success, (5) Average Damage per Round, (6) Assist per Round, (7) Kill: Death, (8) Headshot, and (9) Round on each -each alternative player/competitor. The results of this study are the names of the best players who will be sorted based on the calculation of the total weight and also the alternative statistical values. The results showed that the player who managed to become the Most Valuable Player using F-AHP was TenZ with the highest score of 19.19. The checking in the form of accuracy is carried out by comparing the Fuzzy-AHP calculation and the expert weight value, which is 15%. The case study proves the feasibility and applicability of the proposed methodology for multiple criteria ranking problem. Future research may focus on creating a hierarchy of multilevel attributes to maximize the F-AHP algorithm.