KLASIFIKASI KARAKTER PEMAIN TUNGGAL PUTRA BULU TANGKIS DUNIA BERDASARKAN DATA KOMPETISI BWF MENGGUNAKAN ALGORITMA K-MEANS

Triadi Kurniawan

doi:10.23960/jitet.v14i2.9125

Triadi Kurniawan
Universitas Raharja

DOI: https://doi.org/10.23960/jitet.v14i2.9125

Keywords Bulu Tangkis, BWF, Clustering, Data Mining, K-Means, Badminton

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Abstract

Penelitian ini bertujuan untuk melakukan klasifikasi karakteristik pemain tunggal putra bulu tangkis dunia menggunakan data kompetisi resmi dari Badminton World Federation (BWF) periode 2022-2025. Data sebanyak 190,886 baris diproses melalui tahapan penggabungan, pembersihan, konversi, serta transformasi data menjadi 3,407 profil pemain unik. Algoritma K-Means Clustering diterapkan untuk membagi pemain ke dalam klasifikasi berdasarkan atribut performa yakni peringkat dunia, poin turnamen, dan jumlah partisipasi. Berdasarkan metode Elbow, jumlah klasifikasi optimal yang ditemukan adalah empat (k=4). Hasil penelitian menunjukkan empat klasifikasi dengan tipe karakteristik pemain: Low Exposure Players (44.61%), Beginner Players (42.21%), Developing Players (11.56%), dan Elite Players (1.61%). Evaluasi kualitas klasifikasi menggunakan Silhouette Score menghasilkan nilai 0.519 yang menandakan pemisahan klasifikasi cukup baik, serta Davies-Bouldin Index sebesar 0.641 yang menunjukkan struktur data terpisah dengan jelas. Temuan ini memberikan gambaran peta kekuatan bulu tangkis global, di mana mayoritas atlet dunia masih terkendala minimnya jam terbang turnamen internasional.

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