View Item 
      •   IPB Repository
      • Dissertations and Theses
      • Undergraduate Theses
      • UT - Faculty of Mathematics and Natural Sciences
      • UT - Statistics and Data Sciences
      • View Item
      •   IPB Repository
      • Dissertations and Theses
      • Undergraduate Theses
      • UT - Faculty of Mathematics and Natural Sciences
      • UT - Statistics and Data Sciences
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Penerapan Model Regresi Logistik Biner dan Random Forest terhadap Prospek Atlet Muda pada Liga Basket DBL Tahun 2019

      Thumbnail
      View/Open
      Cover (512.1Kb)
      Fullteks (1.665Mb)
      Lampiran (92.84Kb)
      Date
      2023
      Author
      Muhammad, Marta Nur
      Masjkur, Mohammad
      Aidi, Muhammad Nur
      Metadata
      Show full item record
      Abstract
      Prestasi olahraga merupakan suatu tolak ukur kesuksesan pembinaan suatu cabang olahraga. Hal tersebut dapat terwujud dengan sistem yang sah dan profesional seperti liga basket untuk kalangan pelajar. Kompetisi yang bagus akan mendukung perkembangan prospek atlet. Prospek atlet merupakan kemungkinan yang berdampak di masa mendatang akibat usaha yang dilakukan masa sekarang. Menurut Pedoman Program Indonesia Emas (PRIMA) yang ditetapkan oleh Komite Olahraga Nasional Indonesia ada 2015, atlet pratama merupakan kelompok untuk pembinaan tingkat nasional atau regional. Pemodelan klasifikasi prospek atlet berdasarkan sumber data statistik pertandingan Liga Basket DBL Tahun 2019 menggunakan metode regresi logistik biner dan random forest dengan penerapan teknik penanganan data tidak seimbang dan teknik validasi. Hasil penelitian ini menunjukkan bahwa semua model yang dibentuk memberikan kinerja yang baik serta dapat dikatakan bahwa peubah point yang merepresentasikan kemampuan mencetak angka dan assist yang merepresentasikan kemampuan olah bola merupakan peubah berpengaruh yang konsisten dalam memprediksi prospek atlet muda.
       
      Sports achievement is a measure of the success of coaching a sport. This can be realized with a legal and professional system such as a basketball league for students. Good competition will support the development of athlete prospects. The athlete's prospect is a possibility that will have an impact in the future due to the efforts made in the present. According to the Indonesia Gold Program Guidelines (PRIMA) established by the Indonesian National Sports Committee in 2015, pratama athletes are a group for national or regional level coaching. Modeling the classification of athlete prospects based on statistical data sources for the 2019 DBL Basketball League matches using binary logistic regression and random forest methods with the application of unbalanced data handling techniques and validation techniques. The results of this study indicate that all the models formed provide good performance and it can be said that the point variable which represents the ability to score points and assists which represents the ability to play the ball is a consistent influential variable in predicting the prospects of young athletes.
       
      URI
      http://repository.ipb.ac.id/handle/123456789/117210
      Collections
      • UT - Statistics and Data Sciences [2260]

      Copyright © 2020 Library of IPB University
      All rights reserved
      Contact Us | Send Feedback
      Indonesia DSpace Group 
      IPB University Scientific Repository
      UIN Syarif Hidayatullah Institutional Repository
      Universitas Jember Digital Repository
        

       

      Browse

      All of IPB RepositoryCollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

      My Account

      Login

      Application

      google store

      Copyright © 2020 Library of IPB University
      All rights reserved
      Contact Us | Send Feedback
      Indonesia DSpace Group 
      IPB University Scientific Repository
      UIN Syarif Hidayatullah Institutional Repository
      Universitas Jember Digital Repository