Decision support system for football player's position with tsukamoto fuzzy inference system

• Main Authors: Gerhana Yana Aditia, Zulfikar Wildan Budiawan, Nurrokhman Yuga, Slamet Cepy, Ramdhani Muhammad Ali
• Format: Article
• Language: English
• Published: EDP Sciences 2018-01-01
• Series: MATEC Web of Conferences
• Online Access: https://doi.org/10.1051/matecconf/201819703014

Nowadays, football is one of the most famous sports in the world. Many football clubs and football academies have been established in Indonesia. In football academy, each player will be trained and selected to get the best positon in the team formation. In fact, each player has a different ability and skill. If a player gets a correct position, he can open the opportunity for his team to win a competition. This condition absolutely gives a good impact for the team. However, it will be a serious problem if a player plays in an incorrect position. The player's best position can be deciding by his own ability and skill. This study proposes the selection model of player's position by understanding a player's speed, stamina, strength, and other skills that covering, shooting, passing, dribble, and header with Tsukamoto Fuzzy Inference System. A player may have the following positions: central forward, midfielder, winger, goal keeper. In evaluation phase, this model exactly shows 52.17% accurate value. This means that the model decreases the misplacement of player's position. It is recommended for further study to make some additional criteria such as player's emotion, attitude, etc in order to increase accurate.