HUMAN MOTION DETECTION UNTUK TERJEMAH ‎‎BAHASA ISYARAT MENGGUNAKAN METODE RANDOM ‎‎FOREST

Hilmi, Diki Taufi (2023) HUMAN MOTION DETECTION UNTUK TERJEMAH ‎‎BAHASA ISYARAT MENGGUNAKAN METODE RANDOM ‎‎FOREST. Undergraduate thesis, Universitas Muhammadiyah Malang.

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Abstract

‎ ‎Communication is something extremely vital for social beings such as ‎humans. However, not all humans can perform it normally, and one of the ‎reasons is due to disabilities. Therefore, Sign Language is required in order to ‎maintain communication. Sign language is a language that prioritizes body ‎language and lip movements, not sound, for communication. Deaf individuals are ‎a group that frequently utilizes this language, usually by combining hand ‎movements, finger movements, body movements, and facial expressions to ‎express their thoughts. However, not everyone understands how to communicate ‎using sign language. Hence, a sign language translator detection system is ‎needed to facilitate communication between those who understand sign language ‎and those who do not. This research employs the Random Forest method with the ‎Holistic architecture detected by MediaPipe, using pose estimation to obtain ‎landmarks/keypoints for each input image on the hands, face, and body. The ‎obtained results create a sign language detection system that can be operated in ‎real-time with a high level of accuracy, averaging 97% in each classification.‎

Item Type: Thesis (Undergraduate)
Student ID: 201810130311175
Keywords: Sign Language; SIBI; Random Forest; Python; Holistic
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering > Department of Electrical Engineering (20201)
Depositing User: Diki Taufi Hilmi
Date Deposited: 16 Nov 2023 08:16
Last Modified: 16 Nov 2023 08:16
URI: https://eprints.umm.ac.id/id/eprint/946

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