Design of SIBI Sign Language Recognition Using Artificial Neural Network Backpropagation

Anik Nur Handayani; Muhammad Iqbal Akbar; Harits Ar-Rosyid; Muhammad Ilham; Rosa Andrie Asmara; Osamu Fukuda

doi:10.1109/ICICyTA57421.2022.10038205

Design of SIBI Sign Language Recognition Using Artificial Neural Network Backpropagation

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Anik Nur Handayani, Muhammad Iqbal Akbar, Harits Ar-Rosyid, Muhammad Ilham, Rosa Andrie Asmara, Osamu Fukuda

2022 2022 2nd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2022 Conference paper Cited by 8

Abstract

Humans communicate with one another in the form of language. However, in social life, not all humans, as well as deaf people, can communicate verbally well. They tend to communicate with others using sign language. One of the sign language systems in Indonesia is SIBI. In its application, there are many obstacles when deaf or speech-impaired people communicate with normal people. This happens because of the lack of understanding of sign language in people who do not have special needs. The existence of a sign language translator system can overcome these obstacles. The development of this system utilizes the Neural Network Backpropagation algorithm as its classification algorithm. This research aims to find the best combination of its parameters based on the obtained accuracy. © 2022 IEEE.

Affiliations

Universitas Negeri Malang, Department of Electrical Engineering, Malang, Indonesia; State Polytechnic of Malang, Information Technology Department, Malang, Indonesia; Saga University, Graduate School of Science and Engineering, Saga, Japan

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