PENGELOMPOKAN PERFORMA PEMAIN BASKET DENGAN SELEKSI FITUR NILAI STATISTIK MENGGUNAKAN K-MEANS DAN FUZZY C-MEANS
DOI:
https://doi.org/10.24246/itexplore.v1i3.2022.pp166-178Keywords:
basketball, players’ performance, feature selection, statistical values, k-means, fuzzy c-meansAbstract
Assessment of individual performance in an organization is needed to improve organizational performance, not least in the basketball team. Satya Wacana Saints Salatiga is a basketball team in Indonesia that competes in the Indonesian Basketball League (IBL). All players have statistical values in a basketball game, including points, assists, blocks, rebounds, and steals. These five features can be used as a reference for coaches in determining the performance of players consisting of players with good, moderate, and poor performance. Feature selection determines the feature(s) that most affects a player's performance. In this study, a feature selection of the statistical value of players was carried out to assess the performance of basketball players. The data was obtained from IBL statistical data for the Satya Wacana Saints Salatiga team for the 2021 season. The method used was k-means and fuzzy c-means with feature selection. The experiment results showed that the point value was the main factor influencing players' performance. The comparison between the k-means and fuzzy c-means with the actual performance of the coaches' assessment shows that the fuzzy c-means algorithm has an accuracy rate of 1.0000, while the k-means algorithm is 0.8000. It means that the evaluation of the player's performance can be determined from the point value using the fuzzy c-means algorithm.
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