PERBANDINGAN KLASIFIKASI MULTI ALGORITMA DAN SELEKSI FITUR UNTUK KARAKTERISTIK PEMAIN SEPAK BOLA THE EA SPORT FIFA VIDEO GAME

PERBANDINGAN KLASIFIKASI MULTI ALGORITMA DAN SELEKSI FITUR UNTUK KARAKTERISTIK PEMAIN SEPAK BOLA THE EA SPORT FIFA VIDEO GAME

• By Mustofa;
• Tesis
• 164

Dengan meningkatnya jumlah data terkait pemain sepak bola maka diperlukan sebuah metode yang dapat memberikan informasi yang dibutuhkan secara cepat dan akurat. Data mining menjadi salah satu dalam teknologi informasi yang menjadi tren dengan meningkatnya jumlah data. Data mining sangat penting untuk membantu memberikan masukan sebagai bahan pertimbangan seorang pelatih untuk menentukan posisi bermain seorang pemain sepak bola. Salah satu yang dapat dimanfaatkan adalah algoritma klasifikasi yang dapat digunakan untuk mengelompokan dan menganalisa data pemain sepak bola. Dalam penelitian ini peneliti menggunakan teknik seleksi fitur dan teknik bagging pada beberapa metode untuk melakukan klasifikasi pemain sepak bola dalam empat kelas. Pengelompokan dibagi pada pemain depan, pemain tengah, pemain belakang dan penjaga gawang. Dari hasil penelitian menunjukan bahwa teknik seleksi fitur dan teknik bagging dapat meningkatkan performa akurasi. Metode Random Forest menunjukan nilai akurasi terbaik mencapai 91,3562%.
Kata Kunci:
Machine Learning, Seleksi Fitur, Bagging, Random Forest.
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• Katakunci Machine Learning, Seleksi Fitur, Bagging, Random Forest
• URL http://
• Penerbit ,

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