Sistem Klarifikasi Bahasa Isyarat Indonesia (Bisindo) Dengan Menggunakan Algoritma Convolutional Neural Network
Lukman Arisandi, Barka Satya
Abstract
Communication is needed to interact and socialize in order to connect with the environment and other people. In general, communication uses spoken or written words. However, in some cases in the community there are some people who cannot communicate verbally due to physical limitations such as deaf and speech impaired. Usually, they use nonverbal communication such as body movements and this communication is commonly referred to as sign language. The sign language method is used to spell or pronounce words. However, not everyone can understand the sign language used by the deaf and mute, so a system or tool is needed to bridge communication between the deaf or mute and normal people. One solution that can be offered is the use of computer technology as a tool to identify sign language. The technology is in the form of an automatic language translator system design with processing input images in the form of letter classes A to E, I, You and I Love You using the Convolutional Neural Network (CNN) architecture which by using this method the accuracy value can reach 99.82%.