Aplikasi Penerjemah Bahasa Bangka Ke Bahasa Indonesia Menggunakan Neural Machine Translation Berbasis Website
DOI:
https://doi.org/10.33504/jitt.v1i1.67Keywords:
BLEU scores, flaskmr, corpus paralel, machine translation, RNNAbstract
At this time, machine translation is one of the options for translating languages, especially for people who want to learn a language. Bangka language is a language that is often used by the Bangka people for everyday life. There have been many developments for machine translation, but no one has yet developed a translation machine for the Bangka language. The development of a machine translation using Neural Machine Translation (NMT) and its implementation using the Flask microframework is the first step for the development of a machine translation for the Bangka language. This study aims to make and find out the translation results of the Bangka language translator application into Indonesian using the RNN translator model. The development starts from creating a parallel corpus of Bangka language to Indonesian and machine translation architecture with the RNN model. The research method starts from dataset collection, data preprocessing, modeling and training, system evaluation and implementation. From the results of the BLEU Scores evaluation, a value of 55.3% was obtained for Bangka to Indonesian. Furthermore, the model is implemented in the form of a website by utilizing the Flask framework, so that users can easily translate.
Downloads
References
A. Ginting and N. AZ, "Penerjemah Dua Arah Bahasa Indinonesia Ke Bahasa Daerah," Jurnal Telematika MKOM, 2012.
P. Saputra and M. Afifulloh, "Pemetaan Penggunaan Bahasa Melayu Bangka”, Jurnal Ilmiah Bahasa dan Sastra Terakreditasi, vol. 3, 2020.
S. D. Astuti, "Tafsir Budaya Asak Budu Ge Saro pada Masyarakat Bangka Belitung dalam Perspektif Pendidikan Anak," Tawshiyah: Jurnal Sosial Keagamaan dan Pendidikan Islam, vol. 15, pp. 86-101, 2020.
B. Nothofer, Dialek Melayu Bangka, Malaysia: Universiti Kebangsaan Malaysia, 1997.
D. Bahdanau, K. Cho and Y. Bengio, "Neural machine translation by jointly learning to align and translate," International Conference on Learning Representations, 2015.
S. Yang, Y. Wang and X. Chu, "A Survey of Deep Learning Techniques for Neural Machine Translation," 18 February 2020. [Online]. Available: https://arxiv.org/abs/2002.07526.
R. Sennrich and B. Zhang, "Revisiting Low-Resource Neural Machine Translation: A Case Study," ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, pp. 211-221, 2020.
F. A. Muttaqin and A. M. Bachtiar, "Implementasi Text Mining Pada Aplikasi Pengawasan Penggunaan Internet Anak," Jurnal Ilmiah Komputer dan Informatika (KOMPUTA), 2016.
K. Papineni, S. Roukos, T. Ward and W. J. Zhu, "BLEU: a Method for Automatic Evaluation of Machine Translation," 2002.
Kementrian Pendidikan dan Kebudayaan, Kamus Bahasa Melayu Bangka - Indonesia, Kantor Bahasa Kepulauan Bangka Belitung, 2018.
J. Zhu, Y. Xia, L. Wu, D. He, T. Qin, W. Zhou, H. Li and T.-Y. Liu, "Incorporating BERT into Neural Machine Translation," 17 February 2020. [Online]. Available: ttps://arxiv.org/abs/2002.06823v1.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Jurnal Inovasi Teknologi Terapan
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
