Seleksi Fitur pada Pengelompokan Posisi Pemain Basket menggunakan Fuzzy C-Means

Abstract

Basketball is a well-known sport in the world. Satya Wacana Saint is one of the basketball teams in Indonesia. This team is one of the contestants for the Indonesian Basketball League (IBL). In basketball, players are divided into three main positions according to their physical condition, which are center, forward, and guard. The goal of this research is to select the physical condition features that most influence the player's position. The data used in this paper is data on height, weight, age, and body mass index (BMI) of 23 players. Fuzzy c-means (FCM) clustering is used to group the data into three positions based on their physical condition's features. To find out which feature(s) are the most influential in determining the player's position, we use feature selection with FCM clustering algorithm. For comparison, the FCM results are compared with their actual positions. From the four features of physical condition, it can be concluded that the features of height and BMI are the two most influential features in determining the position of a player. If all features are used in FCM, the accuracy is 0.8696, while if the features of height and BMI are used, the accuracy is higher, i.e., 0.9565.

Feature-reduction Fuzzy c-means Clustering for Basketball Players Positioning

“…Therefore, the ER of the FRFCM clustering result is 0.0435. As a comparison, the result of Erga and Nataliani [19], using the combination of height and BMI, the ER is also 0.0435. As mentioned before, they combined four physical conditions, i.e., height, weight, age, and BMI, one by one to get the best clustering result.…”

“…They combined four physical conditions, i.e., height, weight, age, and BMI, one by one to get the best clustering result, which was measured by the accuracy rate. Height and BMI are the best combinations to determine the player's position [19].…”

“…The center position is more likely to physically collide with opposing players in scoring or blocking the opponent's center position. This position is held by the tallest and biggest player [19].…”

Pengelompokan Performa Pemain Basket Dengan Seleksi Fitur Nilai Statistik Menggunakan K-Means Dan Fuzzy C-Means

“…Metode fuzzy c-means diterapkan untuk mengelompokkan posisi pemain basket berdasarkan dengan fisiknya, yang terdiri dari tinggi badan, berat badan, umur, dan body mass index (BMI). Tinggi badan dan BMI merupakan dua kondisi fisik terpenting dalam penentuan posisi pemain basket [6]. Seorang pelatih basket perlu melihat kesamaan karakteristik gaya permainan para pemainnya untuk menentukan strategi permainan sehingga dapat memenangkan pertandingan.…”

Clustering Performa Pemain Basket Berdasarkan Posisi dan Statistik Pemain Menggunakan Metode Fuzzy c-Means

“…Selain itu terdapat juga penelitian seleksi kriteria untuk mengelompokkan posisi dalam permainan basket dimana pada penelitian ini diseleksi bentuk fisik yang paling mempengaruhi pemain basket itu ditempatkan, yaitu di posisi center, forward, dan guard. Pada penelitian ini didapati dua fitur yang paling berpengaruh dalam menentukan posisi pemain yaitu fitur tinggi badan dan BMI [11]. Penelitian lainnya yaitu penggunaan fuzzy c-means dalam clustering seleksi performa pemain pada tim hockey Kabupaten Kendal untuk mencari potensi dari data personal pada setiap pemain yang akan diclustering ke dalam cluster.…”