Pengembangan Website Speech To Video Bahasa Isyarat Indonesia (Bisindo) Berbasis Algoritma Long Shot Term Memory

Authors

  • Angky Fay Deleviar Universitas Duta Bangsa Surakarta
  • Intan Oktaviani Universitas Duta Bangsa Surakarta
  • Hanifah Permatasari Universitas Duta Bangsa Surakarta

DOI:

https://doi.org/10.29408/jit.v8i1.26117

Keywords:

BISINDO, LSTM, RUP, Speech to text, website, Bisindo Translation

Abstract

Indonesian Sign Language (BISINDO) is an essential communication tool for more than one million deaf people in Indonesia. This research aims to develop a Speech to BISINDO website based on the Long Short-Term Memory (LSTM) algorithm to overcome barriers in communication and learning processes for the deaf community. The research stages include data collection through questionnaires and literature studies to understand user needs, as well as system development using the Rational Unified Process (RUP) method. The system is designed to convert voice input into sign language videos and support the sign language learning process through interactive features. Testing was conducted to ensure that the system meets functional and non-functional needs. The results show that the Speech to BISINDO website is effective in translating speech into sign language videos with high accuracy, as well as supporting better communication and learning between deaf people and the general public. The system offers an innovative solution to improve access to information and learning process for people with hearing impairment.

References

I. P. Sari, Salamun, And Sukri, “Bank Kosa Kata Untuk Tuna Rungu Dan Tuna Wicara Berbasis Web,” J. Appl. Comput. Sci. Technol., Vol. 2, No. 2, Pp. 83–87, 2021, Doi: 10.52158/Jacost.V2i2.250.

D. Afriani, “The Deaf People’s Language,” Sawerigading, Vol. 25, No. 3, Pp. 285–292, 2019.

C. Purnamasari, “Kendala Komunikasi Penyandang Tuna Rungu Melalui Bahasa Isyarat Indonesia Di Kota Semarang,” Repos. Udinus, 2020.

U. Pratama, A. B., Zuliana, R., & Faizah, “Rancang Bangun Aplikasi Kamus Bergambar Sebagai Media Pembelajaran Bahasa Isyarat Indonesia (Bisindo) Bagi Tuna Rungu,” J. Ilm. Teknol. Inf. Terap., Vol. 8, No. 1, Pp. 15–22, 2022.

A. Permana, I.C., Widodo, A., Wibowo, “Sign Language Recognition System Using Convolutional Neural Networks,” Conf. Ser. Mater. Sci. Eng., Vol. 830, No. 2, Pp. 22–32, 2020.

H. N. Siti Nur, Aghisna Nur Assyifa, “Pengembangan Aplikasi Penerjemah Bahasa Isyarat Indonesia (Bisindo) Menggunakan Metode Long-Short Term Memory,” Edusaintek, Vol. 11, No. 1, Pp. 13–30, 2024.

M. Sholawati, K. Auliasari, And F. X. Ariwibisono, “Pengembangan Aplikasi Pengenalan Bahasa Isyarat Abjad Sibi Menggunakan Metode Convolutional Neural Network ( Cnn ),” Jati (Jurnal Mhs. Tek. Inform., Vol. 6, No. 1, Pp. 134–144, 2022.

Fifin Ayu Mufarroha, “Aplikasi Penerjemah Sebagai Media Menggunakan Kombinasi Metode Skin,” J. Simantec, Vol. 9, No. 2, Pp. 57–64, 2021.

D. Gustiar, S. H. Sitorus, D. M. Midyanti, J. Rekayasa, And S. Komputer, “Penerjemahan Bahasa Isyarat Menggunakan Metode Generalized Learning Vector Quantization ( Glvq ) Abstrak 2 Landasan Teori Learning Vector Quantization,” Coding J. Komput. Dan Apl., Vol. 8, No. 03, Pp. 1–8, 2020.

A. Aljabar, “Bisindo ( Bahasa Isyarat Indonesia ) Sign Language Recognition Using Cnn And Lstm,” Adv. Sci. Technol. Eng. Syst. J., Vol. 5, No. 5, Pp. 282–287, 2020.

A. Dwi Baitur Rizky, M. Aulia Faqihuddin, F. Fatha Romadhan, And I. Agustien Siradjuddin, “Identifikasi Alfabet Bahasa Isyarat Indonesia Dengan Menggunakan Convolutional Lstm,” Pros. Seniati, Vol. 7, No. 2, Pp. 183–190, 2023, Doi: 10.36040/Seniati.V7i2.7925.

A. Azis And I. Rahim, “Analisis Penggunaan Bahasa Isyarat Indonesia ( Bisindo ) Pada Siswa Slb,” J. Onoma Pendidikan, Bhs. Dan Sastra, Vol. 9, No. 2, Pp. 1396–1402, 2023.

A. Sherstinsky, “Fundamentals Of Recurrent Neural Network (Rnn) And Long Short-Term Memory (Lstm) Network,” 2020.

J. Wu Et Al., “On Decoder-Only Architecture For Speech-To-Text And Large Language Model Integration,” 2023, Doi: Doi:Https://Doi.Org/10.1109/Asru57964.2023.10389705.

C. Wang, Y. Tang, X. Ma, A. Wu, D. Okhonko, And J. Pino, “S2t : Fast Speech-To-Text Modeling With Fairseq,” Pp. 33–39, 2020.

W. W. Ma’ruf Hasan Nurwahid, Budiman Budiman, “Perancangan Sistem Informasi E-Raport Berbasis Web,” J. Teknol. Dan Sist. Inf. Bisnis, Vol. 5, No. 1, Pp. 36–41, 2023.

I. Sari, E. Altiarika, And E. Altiarika, “Sistem Pengembangan Bahasa Isyarat Untuk Berkomunikasi Dengan Penyandang Disabilitas ( Tunarungu ),” J. Inf. Technol. Soc., Vol. 1, No. 1, Pp. 20–25, 2023.

I. N. Tri, A. Putra, K. S. Kartini, Y. K. Suyitno, And I. M. Sugiarta, “Penerapan Library Tensorflow , Cvzone , Dan Numpy Pada Sistem Deteksi Bahasa Isyarat Secara Real Time,” J. Krisnadana, Vol. 2, No. 3, 2023.

H. Sukri, U. M. Indonesia, S. Informasi, G. Meneng, And K. B. Lampung, “Sistem Informasi Penelitian Dan Pengabdian Dosen Program Studi Sistem Informasi Menggunakan Metode Rational Unified Process ( Rup ),” Altek, Vol. 1, No. 1, 2020.

N. A. Dm, R. Susanto, R. D. Irawan, And V. No, “Infotek : Jurnal Informatika Dan Teknologi Pengembangan Game Terapi Bagi Anak Autisme Berbasis Motion Capture Dengan Metode Optimasi Kalman Filter Infotek : Jurnal Informatika Dan Teknologi Autisme Merupakan Suatu Kondisi Yang Ditandai Dengan Adanya Hamba,” Vol. 7, No. 2, 2024.

Hasim Azari, Dwi Hartanti, And Aprilisa Arum Sari, “Pengelompokan Produksi Padi Dan Beras Provinsi Jawa Timur Dengan Metode Agglomerative Hierarchical Clustering,” Infotek J. Inform. Dan Teknol., Vol. 7, No. 2, Pp. 379–389, 2024, Doi: 10.29408/Jit.V7i2.26016

Downloads

Published

20-01-2025

How to Cite

Deleviar, A. F. ., Intan Oktaviani, & Hanifah Permatasari. (2025). Pengembangan Website Speech To Video Bahasa Isyarat Indonesia (Bisindo) Berbasis Algoritma Long Shot Term Memory. Infotek: Jurnal Informatika Dan Teknologi, 8(1), 23–33. https://doi.org/10.29408/jit.v8i1.26117