Klasifikasi Gerakan Tangan Menjadi Suara Menggunakan Neural Network

Muhammad Arifan Lizamanihi; Ii Munadhif; Mohammad Abu Jami'in

doi:10.21107/rekayasa.v13i3.6614

Klasifikasi Gerakan Tangan Menjadi Suara Menggunakan Neural Network

Muhammad Arifan Lizamanihi, Ii Munadhif, Mohammad Abu Jami'in

Abstract

Indonesian Sign Language (BISINDO) is a language for people with hearing impairment and speech impairment. But sign language still has disadvantages when it is used for people who have never learned sign language that is normal people. Therefore we need a tool in the form of gloves that can translate sign language with sound output. This instrument consists of ten flex sensors, two GY521 sensors, two arduino nano, one arduino mega, a computer and android devices. There is a classification method that is a neural network with data samples of ten hand movements that have meaning (saya, kamu, bapak, ibu, adik, tidur, bertemu, apa, maaf, hari ini) and each hand gesture twenty times. Classification results vary. (saya) get 100% success, (kamu) get 80% success, (bapak) get 60% success, (ibu) get 20% success, (adik) get 90% success, (tidur) get 80% success, (bertemu) get 100% success, (apa) get 70% success, (maaf) get 50% success, and (hari ini) get 90% success. The overall average is 74%.

Keywords

BISINDO; gloves; sensors; arduino; neural network; sound

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