Survei Algoritma Pemrosesan Bahasa Pada Bisindo

  • Nurul Afipah Yardi Universitas Lancang Kuning
  • Guntoro Universitas Lancang Kuning
Keywords: Classification, Bisindo, Deaf

Abstract

BISINDO is known as Indonesian Sign Language and one of the alternative languages used by people with disabilities and developed by deaf people for visual communication. With 6,952,797 deaf people in Indonesia out of a total population of 207,839,035, there are hundreds of thousands of words in Indonesian that can be represented by sign language signs, sign language can be foreign and difficult to understand for some hearing people, both normal and lay people.

The aim of this research is to help lay people classify and detect movements in sign language vocabulary. Classification learning techniques such as machine learning are needed to be able to distinguish changes and various types of gestures in sign language.

Downloads

Download data is not yet available.

References

Ahmad Zuli Amrullah1, K. E. (2019). Analisis dan Perancangan Kamus Interaktif Bahasa Isyarat Indonesia dengan Speech . Jurnal BITe, 110-115.
Aziz, A. N. (2021). IMAGE RECOGNITION ALFABET BAHASA ISYARAT INDONESIA (BISINDO) MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK.
Darmatasia. (2021). Pengenalan sistem isyarat bahasa indonesia (SIBI) menggunakan gardient-convolutional naural network. Jurnal Instek Informatika Teknologi.
Febri Damatraseta Fairuz, R. N. (2021). Real-time BISINDO hand gesture detection and recognition with deep learning CNN. Jurnal Informatika kesatuan, 71-76.
Ika Dyah Agustia Rachmawati, R. Y. (2023). Deep Transfer Learning for Sign Language Image Classification: A Bisindo Dataset Study. binus journal publishing.
Indah Sari, F. E. (2023). Sistem Pengembangan Bahasa Isyarat Untuk Berkomunikasi dengan Penyandang Disabilitas (Tunarungu). Journal of Information Technology and society (JITS).
Kurniawan, A. (2022). APLIKASI SPEECH RECOGNITION SEBAGAI PENGENALAN UCAPAN TUNAWICARA MENGGUNAKAN GOOGLE CLOUD SPEECH API BERBASIS ANDROID.
M reza fauzan azima, r. t. (2019). DETEKSI SISTEM ISYARAT BAHASA INDONESIA HURUF A-Z MENGGUNAKAN METODE YOU ONLY LOOK ONCE DENGAN OUTPUT TEXT. Diploma thesis, Universitas Nasional.
Muliani, A. (2019). Penerapan Teknologi Speech Recognition (Voice to Sign) untuk membantu komunikasi dengan penyandang disabilitas pendengaran. Jurnal Teknovasi, 49-53.
Nadia Intan Pratiwi, ,. I. (2019). Perancangan Sistem Deteksi Isyarat BISINDO Dengan Metode Adaptive Neuro-Fuzzy Inference System (ANFIS). Jurnal KomtekInfo, 50-61.
Nasha Hikmatia A.E, M. I. (2021). Aplikasi Penerjemah Bahasa Isyarat Indonesia Menjadi Suara Berbasis Android Menggunakan Tensorflow. Jurnal Politeknik Caltex Riau, 74-83.
Rachardi, F. (2020). Deteksi gambar gestur kosakata .
Robby Kamil, A. (2021). Perancangan Aplikasi Bahasa Isyarat “Isyaratku” Dengan Deep Learning Serta Google Cloud Platform. Jurnal Sistem Informasi dan Informatika .
Tri Handhika, I. S. (2019). Pendekatan Machine Learning dalam Pengenalan Bahasa Isyarat Indonesia. Sanga Sanga Grup.
Published
2023-12-31
How to Cite
Nurul Afipah Yardi, & Guntoro. (2023). Survei Algoritma Pemrosesan Bahasa Pada Bisindo. SEMASTER: Seminar Nasional Teknologi Informasi & Ilmu Komputer, 2(1), 255-264. Retrieved from https://journal.unilak.ac.id/index.php/Semaster/article/view/18562
Abstract viewed = 5 times
PDF downloaded = 1 times

Most read articles by the same author(s)

1 2 > >>