Sistem Klarifikasi Bahasa Isyarat Indonesia (Bisindo) Dengan Menggunakan Algoritma Convolutional Neural Network
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%.
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