MACHINE LEARNING PADA RANCANG BANGUN SISTEM PENERJEMAH BAHASA ISYARAT MENGGUNAKAN SARUNG TANGAN ELEKTRONIK BERBASIS APLIKASI
| Main Author: | Nizam, Mohamad |
|---|---|
| Format: | Thesis NonPeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
http://eprints.umm.ac.id/61055/1/PENDAHULUAN.pdf http://eprints.umm.ac.id/61055/2/BAB%20I.pdf http://eprints.umm.ac.id/61055/3/BAB%20II.pdf http://eprints.umm.ac.id/61055/4/BAB%20III.pdf http://eprints.umm.ac.id/61055/5/BAB%20IV.pdf http://eprints.umm.ac.id/61055/6/BAB%20V.pdf http://eprints.umm.ac.id/61055/7/LAMPIRAN.pdf http://eprints.umm.ac.id/61055/8/Poster.pdf http://eprints.umm.ac.id/61055/ |
Daftar Isi:
- Communication is the main pillar in human interaction. In the dynamics of communication, effective or not a communication depends on individual conditions. Some people have limitations in communication, both caused by physically or mentally. Individuals who have limitations in communication, use sign language to communicate. However, not everyone understands sign language, so the communication between individuals who have limitation and normal individuals becomes ineffective. In this study, the expected output is an application integrated with electronic gloves that can be translated sign language into text and speech. This sign language application can bridge communication between normal individuals and individuals who have limitations in communication. The application in this study can translate 37 sign language gestures consisting of numbers (0-10) and letters (A - Z). To translate the sign language, this application uses machine learning to predict the meaning of sign language movement. To make the application easy to use, the output of the prediction converted into a speech, so that the communicant can immediately understand the sign language that was demonstrated.