Aplikasi Penerjemah Bahasa Isyarat Indonesia Ke Dalam Huruf Abjad

Mughaffir Yunus; yusril anwar

doi:10.31850/jsilog.v2i1.1726

Mughaffir Yunus Universitas Muhammadiyah Parepare
yusril anwar Universitas Muhammadiyah Parepare

DOI: https://doi.org/10.31850/jsilog.v2i1.1726

Keywords: BISINDO;, MobileNetV2, Tensorflow, Android, Convolutional Neural Network

Abstract

Sign language is the language used by people with limited speech or hearing. However, not everyone knows how to translate sign language in letters. Therefore, this research is motivated because there are many people who are normal or who do not have disabilities in speaking or listening who do not know how to communicate with people who have these limitations. So from this i raised a topic for the final project, "Application of Indonesian Sign Language Into Alphabet Letters. By using the Convolutional Neural Network classification method using the MobilenetV2 model architecture. The results of the classification will be exported into a model which will then be processed using Tensorflow Lite Android Studio. Based on the results of model testing, the resulting accuracy level reaches 0.9995 with a loss value of 0.6982. So that the performance of the application detection is not optimal. In addition, this application also displays animated letters of the Indonesian sign language alphabet so that people can also learn Indonesian sign language in visual form.

References

Khesya, N. “mengenal flowchart dan pseudocode dalam algoritma dan pemrograman..“ OSF Preprints, hal 7-15, 29 Dec. 2021. [https://doi.org/10.31219/osf.io/dq45e]

Luh Putu Ary Sri Tjahyanti, Gede Danu Setiawan. “perancangan media pembelajaran bahasa isyarat merangkai kalimat penyandang disabilitas anak tunarungu wicara berbasis web.” DAIWI WIDYA Jurnal Pendidikan Vol.06 No.3, hal 44-57, Edisi Desember 2019

Rinaldi, R “penerapan unified modelling language (uml) dalam analisis dan perancangan aplikasi e-learning Simtika, 2(1) Vol. 2 No. 1 2019, hal 43–50, januari 2019

Nurul Adha Oktarini Saputri, Nurul Huda. “Aplikasi Pembelajaran Bahasa Isyarat bagi Penyandang Disabilitas Tunarungu Berbasis Desktop.” JUSIFO (Jurnal Sistem Informasi), p-ISSN: 2460-092X, e-ISSN: 2623-1662 Nomor 1, hal. 77 – 88, Juni 2018

R. A. Mursita, "Respon Tunatungu Terhadap Penggunaan Sistem Bahasa Isyarat Indonesia (SIBI) dan Bahasa Isyarat Indonesia (BISINDO)," INKLUSI Journal of Disability Studies, vol. 2, hal. 221-232, 2019.

Stella Makahaube, Alwin M. Sambul, Sherwin R.U.A. Sompie. “Implementation of Gesture Recognition Technology for Automated Education Service Kiosk Jurnal Teknik Informatika vol. 16 no. 4, hal. 465-472 , October –December 2021. [https://doi.org/10.35793/jti.16.4.2021.34210]

Risnaldy Fatwa Muharram. “implementasi artificial intelligence untuk deteksi masker secara realtime dengan tensorflow dan ssd mobilenet berbasis python.” ,JRKT (Jurnal Rekayasa Komputasi Terapan) Vol 01 No 03 Tahun 2021, hal 139-146.

Vol 01 No 03 Tahun 2021 Khurniawan Eko Saputro “Analisis dan Perancangan Kamus Interaktif Bahasa Isyarat Indonesia dengan Speech Recognition,”. e-ISSN.2685-4066 Vol.1 No.2, hal 110-115 31 Desember 2019

R. I. Borman and B. Priyopradono, “Implementasi Penerjemah Bahasa Isyarat Pada Bahasa Isyarat Indonesia ( BISINDO ) Dengan Metode Principal Component Analysis ( PCA ),” J. Pengemb. IT, vol. 03, no. 1, hal. 103–108, 2018.

Reni Rahmadewi, Endah purwanti, Vita efelina. “identifikasi jenis tumbuhan menggunakan citra daun berbasis jaringan saraf tiruan (artificial neural networks).” Jurnal Media Elektro, hal. 38 - 43, Oct. 2018.

Amka. “Implementasi Pendidikan Karakter Inklusif Bagi Anak Berkebuthan Khusus Di Sekolah Reguler”. Jurnal Disabilitas, Jilid 1, No. 1 Juli 2017,hlm. 1-9

M. I. Zul, "Feature Extraction For Hand Shape Recognition By Using IP Camera," In Regional Conference on Computer and Information Engineering, 2018