Pengembangan Model Deteksi Pelanggaran Servis Ketinggian dan Gerakan Ganda pada Bulutangkis dengan Menggunakan Metode Deep Learning

Sugestino, Adityo (2025) Pengembangan Model Deteksi Pelanggaran Servis Ketinggian dan Gerakan Ganda pada Bulutangkis dengan Menggunakan Metode Deep Learning. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Permainan bulutangkis merupakan salah satu olahraga yang populer di dunia, khususnya di Indonesia. Salah satu aspek penting dalam permainan bulutangkis adalah peraturan servis, di mana pelanggaran terhadap aturan ini dapat memengaruhi jalannya pertandingan secara signifikan. Penilaian terhadap pelanggaran servis, seperti pelanggaran ketinggian serta gerakan ganda (double swing) saat ini masih bergantung pada pengamatan wasit, yang rentan terhadap kesalahan manusia. Untuk mengatasi permasalahan ini, penelitian ini mengembangkan model deteksi pelanggaran servis secara otomatis dengan menggabungkan computer vision serta metode Deep Learning. Penggunaan model Deep Learning YOLO, digunakan untuk menganalisis data video per-frame dan mendeteksi berbagai jenis pelanggaran servis secara real-time. Hasil penelitian menunjukkan bahwa model ini memiliki akurasi yang cukup tinggi dalam mendeteksi pelanggaran servis dibandingkan dengan pengamatan manual oleh wasit. Pengembangan model ini diharapkan dapat meningkatkan kualitas penilaian dalam pertandingan bulutangkis dan memberikan kontribusi terhadap penerapan sport technology dalam dunia olahraga
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Badminton is one of the most popular sports in the world, especially in Indonesia. One important aspect of badminton is the serving rule, where violations of this rule can significantly affect the course of the match. The assessment of service violations, such as height violations as well as double swing movements currently still relies on referee observations, which are prone to human error. To overcome this problem, this research develops an automatic service violation detection model by combining computer vision and Deep Learning methods. The YOLO Deep Learning model is used to analyze video data on a per-frame basis and detect various types of service violations in real-time. The results show that this model has a fairly high accuracy in detecting service violations compared to manual observation by the referee. The development of this model is expected to improve the quality of judgment in badminton matches and contribute to the application of sport technology in the world of sports.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Deep Learning, Servis, Pelanggaran Servis, Computer Vision, YOLO, Deep Learning, Service, Service Violation , Computer Vision, YOLO
Subjects:	Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science)
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User:	Adityo Sugestino
Date Deposited:	01 Aug 2025 01:29
Last Modified:	01 Aug 2025 01:29
URI:	http://repository.its.ac.id/id/eprint/123345

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