Deteksi Gerakan Fitness Menggunakan Pose Estimation Dan YOLOv11

Authors

  • Mealdi Arwintoro Universitas Nusantara PGRI Kediri Indonesia
  • Ardi Sanjaya Universitas Nusantara PGRI Kediri Indonesia
  • Risky Aswi Ramadhani Universitas Nusantara PGRI Kediri Indonesia

DOI:

https://doi.org/10.29407/6sdt7546

Abstract

 Penelitian ini bertujuan untuk mengembangkan sistem deteksi gerakan Fitness secara otomatis menggunakan metode pose estimation estimation dan implementasi YOLOv11. Tujuan utama dari penelitian ini adalah mengidentifikasi dua kelompok gerakan utama dalam aktivitas Fitness yaitu latihan otot kaki dan latihan otot punggung. Pose estimation estimation digunakan untuk mendeteksi titik-titik tubuh dari video gerakan Fitness, sedangkan YOLOv11 digunakan untuk klasifikasi gerakan berdasarkan pola pergerakan tubuh. Dataset terdiri dari 13 jenis latihan yang dibagi menjadi dua kelompok utama: otot kaki (cabble front raise, cabble row, deltoid press, dumble row, lat pulldown, t-bar row) dan otot punggung (hai squat, lunges, leg extension, leg press, squat, standing calf raise, sumo squat). Hasil penelitian menunjukkan bahwa kombinasi metode ini mampu mencapai akurasi klasifikasi rata-rata di 73,3%. Sistem ini dapat dimanfaatkan sebagai alat bantu dalam memonitor dan mengevaluasi gerakan Fitness secara mandiri.

 

Keywords:

Deteksi Gerakan, Fitness, Pose estimation estimation, YOLOv11

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Published

2025-07-10

Issue

Vol. 9 No. 2 (2025): Prosiding Seminar Nasional Inovasi Teknologi Tahun 2025

Section

Articles

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Copyright (c) 2025 Mealdi Arwintoro, Ardi Sanjaya, Risky Aswi Ramadhani

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How to Cite

Deteksi Gerakan Fitness Menggunakan Pose Estimation Dan YOLOv11. (2025). Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), 9(2), 1215-1222. https://doi.org/10.29407/6sdt7546