PENGENALAN ALFABET A-Z BAHASA ISYARAT AMERICAN SIGN LANGUAGE MENGGUNAKAN METODE SUPPORT VECTOR MACHINE

RASUANDI, MUHAMMAD and Fachrurrozi, Muhammad and Primanita, Anggina (2023) PENGENALAN ALFABET A-Z BAHASA ISYARAT AMERICAN SIGN LANGUAGE MENGGUNAKAN METODE SUPPORT VECTOR MACHINE. Undergraduate thesis, Sriwijaya University.

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Abstract

Deafness is a condition where a person's hearing cannot function normally. As a result, these conditions affect ongoing interactions, making it difficult to understand and convey information. Communication problems for the deaf are handled through the introduction of various forms of sign language, one of which is American Sign Language. Computer Vision-based sign language recognition often takes a long time to develop, is less accurate, and cannot be done directly or in real-time. As a result, a solution is needed to overcome this problem. In the system training process, using the Support Vector Machine method to classify data and testing is carried out using the RBF kernel function with C parameters, namely 10, 50, and 100. The results show that the Support Vector Machine method with a C parameter value of 100 has better performance. This is evidenced by the increased accuracy of the RBF C=100 kernel, which is 99%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Bahasa Isyarat, American Sign Language, Support Vector Machine
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) > T11 General works > T11.5 Translating T Technology > T Technology (General) > T10.5-11.9 Communication of technical information > T11 General works > T11.5 Translating T Technology > T Technology (General) > T10.5-11.9 Communication of technical information > T11.5 Translating
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Rasuandi
Date Deposited:	12 May 2023 03:37
Last Modified:	12 May 2023 03:37
URI:	http://repository.unsri.ac.id/id/eprint/101458

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