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All Journal Competitor : Jurnal Pendidikan Kepelatihan Olahraga JOURNAL SPORT AREA JSKK (Jurnal Sains Keolahragaan dan Kesehatan) ACTIVE: Journal of Physical Education, Sport, Health and Recreation jurnal ilmu keolahragaan Jurnal Kepelatihan Olahraga Citius: Jurnal Pendidikan Jasmani, Olahraga, Dan Kesehatan Bajra : Jurnal Keolahragaan Prosiding Seminar Nasional Pascasarjana
Utama, Made Bang Redy
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Gender-based differences in physical fitness profiles of sepak takraw athletes: A multivariate and machine learning analysis Raharjo, Agus; Adi S; Ihsani, Sri Indah; Utama, Made Bang Redy; Appukutty, Mahenderan
Journal Sport Area Vol 11 No 2 (2026): August
Publisher : UIR Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/sportarea.2026.vol11(2).24736

Abstract

Background: Gender differences in physical fitness are well documented in sports science; however, most studies rely on univariate statistical approaches and provide limited insight into multidimensional performance profiles. The application of multivariate and machine learning techniques in sport-specific contexts such as sepak takraw remains limited. Objectives: This study aims to analyse the differences in physical performance between male and female athletes. This study investigates the physical variables that differentiate male and female sepak takraw athletes using a quantitative ex post facto design. Methods: A total of 163 competitive sepak takraw athletes (81 male and 82 female). The sample consists of male and female athletes who underwent a series of physical measurements, including muscle strength, speed, endurance, and agility. Data analysis was conducted using an independent t-test to measure gender differences, Principal Component Analysis (PCA) to explore the  data structure, and a random forest classifier to identify the variables most contributing to gender classification. Results: Significant gender differences were observed in Jump DF, Back Dynamometer, Sprint 30 m, and 1600 m Run (p < 0.01; d = 1.34-2.48). PCA revealed two dominant components (strength–power and endurance), while Random Forest identified back strength as the most influential classification variable (importance = 0.224). The composite index provided a simplified representation of multidimensional performance profiles. Conclusion: The integration of multivariate and machine learning approaches provides a more comprehensive understanding of physical performance profiles in sepak takraw. The proposed composite index offers a practical tool for simplifying complex fitness data and supporting evidence-based training strategies.
Co-Authors Adi S Adi S Adi, Adi S Agus Raharjo Ahmad Sulaiman Aljriad, Hilmi Arba, Fasi Kulisan Asri, Del Fahri, Achmad Syakur Fastabikulkhoirot, Fastabikulkhoirot Festiawan, Rifqi Guntur Firmansyah Guntur Firmansyah Hilmy Aliriad I Gusti Putu Ngurah Adi Santika Ibrahim, Saipulloh Ihsani, Sri Indah Iwan Setiawan Mahenderan Appukutty Maryoto Subekti Nanda, Fitri Agung Novriansyah Novriansyah, Novriansyah Nugraha, Pratama Dharmika Rahmatullah, Muhammad Imam Ramadhan, Muhammad Gilang Rohmad Apriyanto Sigit Dwi Andrianto Wenly, Ayu Purnama Yopi Hutomo Bhakti