Penerapan YOLOv11 untuk Penghitungan Otomatis Jumping Jack pada Video Latihan Fisik

Authors

  • Bradika Almandin Wisesa Politeknik Manufaktur Negeri Bangka Belitung
  • Vivin Mahat Putri Politeknik Manufaktur Negeri Bangka Belitung
  • Evvin Faristasari Politeknik Manufaktur Negeri Bangka Belitung
  • Sirlus Andreanto Jasman Duli Politeknik Manufaktur Negeri Bangka Belitung
  • Indra Irawan Politeknik Manufaktur Negeri Bangka Belitung
  • Silvia Agustin Politeknik Manufaktur Negeri Bangka Belitung

DOI:

https://doi.org/10.47747/jpsii.v6i3.2795

Keywords:

YOLOv11, Jumping Jack Counter, Pengolahan Citra, Deteksi Gerakan

Abstract

The Jumping Jack Counter is an image processing-based application developed to automatically count the number of jumping jack movements in exercise videos. This study aims to implement the YOLOv11 model to detect and count jumping jack movements by analyzing body posture. YOLOv11 is utilized to identify body positions categorized into two main classes: "open" (arms and legs spread apart) and "closed" (arms and legs together). The dataset consists of 15,000 video frames collected from various exercise videos, with research stages including data collection, data labeling, preprocessing, model training, and testing. The results demonstrate that YOLOv11 achieves a 92% accuracy rate in counting jumping jack movements. These findings are expected to assist coaches and users in monitoring physical exercise in real-time, thereby enhancing training effectiveness. The majority of movement detections (78%) were for the open position, followed by the closed position (20%), with 2% detection errors attributed to lighting variations or camera angles. [1].

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Published

2025-07-07

How to Cite

Wisesa, B. A., Putri, V. M. ., Faristasari, E. ., Duli, S. A. J. ., Irawan, I. ., & Agustin, S. . (2025). Penerapan YOLOv11 untuk Penghitungan Otomatis Jumping Jack pada Video Latihan Fisik. Jurnal Pengembangan Sistem Informasi Dan Informatika, 6(3), 91 - 99. https://doi.org/10.47747/jpsii.v6i3.2795