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Journal : The Indonesian Journal of Computer Science

Klasifikasi Gerakan Olahraga Panahan Menggunakan YOLO dan Metode LSTM Adriansyah, Ahmad Rio; Wibowo, Edi; Panji, Krisna
The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i3.4664

Abstract

The classification of archery movements presents a significant challenge in the development of technology to support athlete training. This study aims to develop an archery movement classification system using a combination of YOLO for pose detection and Long Short-Term Memory (LSTM) for temporal classification. The system processes archery training videos into a sequence of images. The aim of this research is to train LSTM model to recognize patterns from four predefined archery movement classes: stand, extend, hold, and release. Evaluation results show that the system achieved an accuracy of 64.47%. Furthermore, analysis using precision, recall, and F1-score metrics indicates varying performance across the movement classes, with the highest F1-score of 83.75% achieved in the release class. This study contributes to the development of machine learning-based technology to support sports training, particularly in archery, by offering a data-driven approach capable of automatically recognizing and evaluating athletes' movements.