An Alternative Soft Set Approach for Identifying Football Conflict: A Case Study of Indonesian Football Super League

Abstract

Conflict situations in football have become a significant issue because they affect the players, supporters, referees, management team, the governing body of football, and the government. As time passes, the discovery of conflicts within the football industry has also become increasingly diverse; both affected in-game or out of the game. In 2015, Indonesia had no activity in football for almost a year when the International Federation of Association Football (FIFA) banned the Football Association of Indonesia (PSSI) from competing in international competitions until the conflict among their internal agents was resolved. The agents involved in this highly controversial ban include the Commission 10 of the Parliament of Indonesia, the National Sports Committee of Indonesia (KONI), the Indonesian President, and the Ministry of Youth and Sport of Indonesia. Conflict resolution strategies outside the football games are delicate and more challenging to overcome due to the involvement of the government and various governing bodies. This opens to higher unpredictability in modeling the conflict situations, hence a lower possibility of a successful conflict resolution model strategy. In addressing this gap, this paper proposes a new Computational Intelligence approach based on the Soft Set Theory, where an alternative algorithm is derived from modeling the conflict situations. We then delineated the proposed algorithm for an instructional example of the Indonesian football conflict situation in 2015 concerning the Indonesia Football Super League. The results showed that the proposed algorithm successfully handled conflict and recommended the Indonesian football agents involved, including PSSI and FIFA.