APLIKASI PENERJEMAH BAHASA ISYARAT BISINDO MENGGUNAKAN METODE YOLOv5 BERBASIS MOBILE

This research aims to develop a mobile application that is able to recognize and translate BISINDO in real-time using the YOLOv5 method. YOLOv5 (You Only Look Once version 5) is an efficient and fast object detection algorithm, making it suitable for implementation on mobile devices. In developing this application, we collected and labeled a typical BISINDO dataset, then trained the YOLOv5 model to detect and recognize these characteristics. The test results show that the implemented model has high accuracy in recognizing various BISINDO characteristics. Apart from that, this application is also designed with an intuitive and easy-to-use user interface, so that users can quickly and easily communicate with people using sign language. With this application, it is hoped that it can expand communication access for people with hearing impaired and increase their social inclusion in society. Further research is needed to continue improving the app's accuracy and efficiency and adding more features that support different user needs.

Authors

Publication Details

Journal
Jurnal SPEKTRUM
Published
2024-09-30
DOI
https://doi.org/10.24843/spektrum.2024.v11.i03.p2
Primary Topic
Multimedia Learning Systems
Type
article
Field-Weighted Citation Impact
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article

APLIKASI PENERJEMAH BAHASA ISYARAT BISINDO MENGGUNAKAN METODE YOLOv5 BERBASIS MOBILE

Duman Care Khrisne, Agus Setyo Budi, I Made Arsa Suyadnya, Albinus Silalahi et al.
Jurnal SPEKTRUM
Multimedia Learning Systems
article

APLIKASI PENERJEMAH BAHASA ISYARAT BISINDO MENGGUNAKAN METODE YOLOv5 BERBASIS MOBILE

Duman Care Khrisne, Agus Setyo Budi, I Made Arsa Suyadnya, Albinus Silalahi, Made Sudarma, Januaray Satya Ega, Wayan Yoga Adi Pranata
article en

Abstract

This research aims to develop a mobile application that is able to recognize and translate BISINDO in real-time using the YOLOv5 method. YOLOv5 (You Only Look Once version 5) is an efficient and fast object detection algorithm, making it suitable for implementation on mobile devices. In developing this application, we collected and labeled a typical BISINDO dataset, then trained the YOLOv5 model to detect and recognize these characteristics. The test results show that the implemented model has high accuracy in recognizing various BISINDO characteristics. Apart from that, this application is also designed with an intuitive and easy-to-use user interface, so that users can quickly and easily communicate with people using sign language. With this application, it is hoped that it can expand communication access for people with hearing impaired and increase their social inclusion in society. Further research is needed to continue improving the app's accuracy and efficiency and adding more features that support different user needs.

Jurnal SPEKTRUMVol. 11(3)
Openalex Percentile: Top 68%
Multimedia Learning Systems
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APLIKASI PENERJEMAH BAHASA ISYARAT BISINDO MENGGUNAKAN METODE YOLOv5 BERBASIS MOBILE — Duman Care Khrisne, Agus Setyo Budi, et al. · Jurnal SPEKTRUM (2024) | TGRS Research Map | TGRS