CLUSTER ANALYSIS UNTUK MEMPREDIKSI TALENTA PEMAIN BASKET MENGGUNAKAN JARINGAN SARAF TIRUAN SELF ORGANIZING MAPS (SOM)

Basketball World has grown rapidly as the time goes on. This is signed by many competition and game all over the world. With the result there are many basketball players with their different playing characteristics. Demand for a coach or scout to look for or search great players to make a solid team...

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Veröffentlicht in:Jurnal informatika 2008-01, Vol.9 (1), p.23-32
Hauptverfasser: Gregorius Satia Budhi, Liliana Liliana, Steven Harryanto
Format: Artikel
Sprache:eng
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Zusammenfassung:Basketball World has grown rapidly as the time goes on. This is signed by many competition and game all over the world. With the result there are many basketball players with their different playing characteristics. Demand for a coach or scout to look for or search great players to make a solid team as a coach requirement. With this application, a coach or scout will be helped in analyzing in decision making. This application uses Self Organizing Maps algorithm (SOM) for Cluster Analysis. The real NBA player data is used for competitive learning or training process and real player data from Indonesian or Petra Christian University Basketball Players is used for testing process. The NBA Player data is prepared through cleaning process and then is transformed into a form that can be processed by SOM Algorithm. After that, the data is clustered with the SOM algorithm. The result of that clusters is displayed into a form that is easy to view and analyze. This result can be saved into a text file. By using the output / result of this application, that are the clusters of NBA player, the user can see the statistics of each cluster. With these cluster statistics coach or scout can predict the statistic and the position of a testing player who is in the same cluster. This information can give a support for the coach or scout to make a decision. Abstract in Bahasa Indonesia : Dunia bola basket telah berkembang dengan pesat seiring dengan berjalannya waktu. Hal ini ditandai dengan munculnya berbagai macam dan jenis kompetisi dan pertandingan baik dunia maupun dalam negeri. Sehingga makin banyak dilahirkannya pemain berbakat dengan berbagai karakteristik permainan yang berbeda. Tuntutan bagi seorang pelatih/pemandu bakat, untuk dapat melihat secara jeli dalam memenuhi kebutuhan tim untuk membentuk tim yang solid. Dengan dibuatnya aplikasi ini, maka akan membantu proses analisis dan pengambilan keputusan bagi pelatih maupun pemandu bakat Aplikasi ini menggunakan algoritma Self Organizing Maps (SOM) untuk melakukan analisis cluster. Data real pemain NBA digunakan untuk keperluan proses training dan data real pemain Indonesia /pemain Universitas Kristen Petra untuk proses testing. Data pemain NBA dipersiapkan dengan melalui proses cleaning dan di transformasi ke bentuk yang dapat diolah oleh algoritma SOM. Kemudian data diolah menggunakan algoritma SOM untuk menghasilkan cluster-cluster data. Hasil cluster-cluster ini ditampilkan dalam bentuk yang mudah untuk dilihat da
ISSN:1411-0105