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All Journal Jambura Health and Sport Journal Jurnal Ilmiah Multidisiplin Ilmu
Martinez Edison Putra
Universitas Katolik Santo Agustinus Hippo
Health Professions Other

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BODY MASS INDEX DAN PANJANG TUNGKAI SEBAGAI PREDIKTOR KELINCAHAN PADA ATLET BOLA VOLI REMAJA Martinez Edison Putra; Jayadi Jayadi; Ibrah Fastabiqi Bawana Mukti; Siskariyanti Siskariyanti
Jambura Health and Sport Journal Vol 8, No 2 (2026): Agustus
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37311/jhsj.v8i2.32578

Abstract

Kelincahan merupakan komponen biomekanik yang peting dalam bola voli, namun penelitian mengenai prediktor antropometriknya terutama Body Mass Index (BMI) dan panjang kaki pada atlet bola voli remaja masih sangat terbatas. Kenyataannya, para pelatih sering kali kesulitan Menyusun program seleksi dan latihan berdasarkan data antropometrik karena kurangnya pengetahuan empiris yang kontekstual. Tujuan dari studi korelasi cross-sectional ini Adalah untuk mengidentifikasi hubungan antara BMI, Panjang kaki, dan kelincahan pada atlet bola voli remaja. Sebanyak 24 atlet amatir laki-laki Sekolah Menengah Kejuruan (SMK) Maniamas Ngabang direkrut melalui metode sampling lengkap. BMI dihitung berdasarkan berat badan dan tinggi badan, Panjang kaki diukur dari spina iliaca anterior superior hingga malleolus medialis, dan kelincahan dievaluasi menggunakan tes heksagonal. Analisis korelasi Pearson menemukan hubungan negative yang signifikan antara BMI dan kelincahan (r = -0,545; p = 0,006) serta hubungan positif yang tidak signifikan antara panjang kaki dan kelincahan (r = 0,335; p = 0,110). Kedua faktor ini menjelaskan 24,4% variasi dalam kelincahan (R2 yang disesuaikan = 0,244; p = 0,020). Temuan ini menunjukkan bahwa pengelilaan komposisi tubuh merupakan aspek penting dalam pengembangan atlet muda, dan memberikan landasan empiris bagi pelatih serta praktisi kedokteran olahraga untuk merancang program latihan dan seleksi berbasis antropometri yang lebih disesuaikan.
Pemetaan Riset Identifikasi Bakat Olahraga Berbasis Teknologi di Indonesia: Tinjauan Sistematis Berbasis Scopus Martinez Edison Putra; Ella Fauziah
Jurnal Ilmiah Multidisiplin Ilmu Vol. 3 No. 4 (2026): Agustus : Jurnal Ilmiah Multidisiplin Ilmu (JIMI)
Publisher : CV. Denasya Smart Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69714/2df4zk12

Abstract

Talent identification in sports is a critical component of modern athlete development. While artificial intelligence (AI) and machine learning (ML) have transformed talent identification practices globally, Indonesia’s contribution to this field remains limited. This study aims to map the current landscape of technology-based sports talent identification research in Indonesia indexed in Scopus. This study employed Systematic Literature Review (SLR) using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. A structured search was conducted in the Scopus database using keywords “sport talent identification” AND “artificial intelligence” OR “machine learning” OR “software”, with inclusion criteria limited to Indonesian-authored articles published between 2016 and 2026. Article selection followed the PICO framework (Population, Intervention, Comparison, Outcome). Four articles met all inclusion criteria. Two articles (50%) employed Research and Development (R&D) approaches developing Android-based and software-based (TIDev) talent identification tools, one articles (25%) utilized a quantitative exploratory design examinging technology policy integration, and one article (25%) applied a machine learning Decision Tree algorithm for football position prediction. All selected technologies demonstrated adequate validity and accuracy, with Cronbach Alpha values of 0.844-0.761, I-CVI score of 0.88-0.93, and a Decision Tree accuracy of 76% with an F1-score of 75%. Notably, no Indonesia Scopus-indexed article specifically implementing artifical intelligence (deep learning or neural networks) for sports talent identification was found. technology-based software and machine learning approaches in Indonesian sports talent identification have demonstrated promosing validity and accuracy. However, the complete absence of AI-based research represents a significant evidence gap and a strategic oppotunity for Indonesian researchers to developp AI-driven talent identification system in support of national sports development programs.
Co-Authors Ella Fauziah Ibrah Fastabiqi Bawana Mukti Jayadi Jayadi Siskariyanti Siskariyanti