Implementation of Neural Machine Translation in Translating from Indonesian to Sasak Language
DOI:
https://doi.org/10.30812/matrik.v23i2.3465Keywords:
Corpus Source Collection, Dataset, Neural Machine Translation, Sasak Regional LanguageAbstract
Language translation is part of Natural Language Processing, also known as Machine Translation, which helps the process of learning foreign and regional languages using translation technology in sentence form. In Lombok, there are still people who are not very fluent in Indonesian because Indonesian is generally only used at formal events. This research aimed to develop a translation model from Indonesian to Sasak. The method used was the Neural Machine Translation with the Recurrent Neural Network - Long Short Term Memory architecture and the Word2Vec Embedding with a sentence translation system. The dataset used was a parallel corpus from the Tatoeba Project and other open sources, divided into 80% training and 20% validation data. The result of this research was the application of Neural Machine Translation with the Recurrent Neural Network - Long Short Term Memory algorithm, which could produce a model with an accuracy of 99.6% in training data and 71.9% in test data. The highest ROUGE evaluation metric result obtained on the model was 88%. This research contributed to providing a translation model from Indonesian to Sasak for the local community to facilitate communication and preserve regional language culture.
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References
[1] V. L. Kane, “Interpretation and machine translation towards google translate as a part of machine translation and teaching
translation,†Applied Translation, pp. 10–17, 2021, https://doi.org/10.51708/apptrans.v15n1.1337.
[2] I. G. A. Budaya, M. W. A. Kesiman, and I. M. G. Sunarya, “Perancangan Mesin Translasi berbasis Neural dari Bahasa Kawi ke
dalam Bahasa Indonesia menggunakan Microframework Flask,†Jurnal Sistem dan Informatika (JSI), pp. 94–103, 2022.
[3] N. Rezaputra and Y. Denny, “Alih Bentuk Kalimat Non-Formal Menjadi Kalimat Formal Menggunakan Pendekatan Machine
Translation,†vol. 8, no. 1, pp. 379–390, 2022.
[4] N. Rezaputra and Y. D. Prabowo, “Alih Bentuk Kalimat Non-Formal Menjadi Kalimat Formal Menggunakan Pendekatan Machine
Translation,†KALBISIANA Jurnal Sains, Bisnis dan . . . , vol. 8, no. 1, pp. 379–390, 2020.
[5] J. C. Hsu, M. Wu, C. Kim, B. Vora, Y. T. Lien, A. Jindal, K. Yoshida, S. Kawakatsu, J. Gore, J. Y. Jin, C. Lu, B. Chen,
and B. Wu, “Applications of Advanced Natural Language Processing for Clinical Pharmacology,†Clinical Pharmacology and
Therapeutics, vol. 0, no. 0, pp. 1–9, 2024, https://doi.org/10.1002/cpt.3161.
[6] A. S. Talita and A.Wiguna, “Implementasi Algoritma Long Short-Term Memory (LSTM) UntukMendeteksi Ujaran Kebencian
(Hate Speech) Pada Kasus Pilpres 2019,†MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 19,
no. 1, pp. 37–44, 2019, https://doi.org/10.30812/matrik.v19i1.495.
[7] Z. Abidin, “Statistical Machine Translation Pada Bahasa Lampung Dialek Api Ke Bahasa Indonesia,†vol. 4, pp. 519–528, 2020,
https://doi.org/10.30865/mib.v4i3.2116.
[8] Y. Fauziyah, R. Ilyas, and F. Kasyidi, “Mesin Penterjemah Bahasa Indonesia-Bahasa Sunda Menggunakan Recurrent Neural
Networks,†Jurnal Teknoinfo, vol. 16, no. 2, p. 313, 2022, https://doi.org/10.33365/jti.v16i2.1930.
[9] L. E. Haris and A. S. Pardiansyah, “Aplikasi Android Kamus Bahasa Indonesia-Sasak,†Jurnal Manajemen Informatika dan
Sistem Informasi, vol. 1, no. 1, p. 1, 2018, https://doi.org/10.36595/misi.v1i1.10.
[10] D. O. Sihombing, “Implementasi Natural Language Processing (NLP) dan Algoritma Cosine Similarity dalam Penilaian Ujian
Esai Otomatis,†Jurnal Sistem Komputer dan Informatika (JSON), vol. 4, no. 2, p. 396, 2022, https://doi.org/10.30865/json.v4i2.
5374.
[11] S. Yang, Y. Wang, and X. Chu, “A Survey of Deep Learning Techniques for Neural Machine Translation.â€
[12] R. A. J. Dabre, C. Chu, and A. Kunchukuttan, “99 A Survey of Multilingual Neural Machine Translation,†vol. 53, no. 5, 2020,
https://doi.org/10.1145/3406095.
[13] Z. Abidin, “Penerapan Neural Machine Translation untuk Eksperimen Penerjemahan secara Otomatis pada Bahasa Lampung
Indonesia,†Prosiding Seminar Nasional Metode Kuantitatif, no. 978, pp. 53–68, 2017.
[14] A. Burhanuddin, A. L. Qosim, and R. Amaliya, “Phrase Based and Neural Network Translation for Text Transliteration from
Arabic to Indonesia,†Matics, vol. 14, no. 1, pp. 13–17, 2022, https://doi.org/10.18860/mat.v14i1.13853.
[15] C. Avci, B. Tekinerdogan, and C. Catal, “Analyzing the performance of long short-term memory architectures for malware
detection models,†Concurrency and Computation: Practice and Experience, vol. 35, no. 6, p. 1, 2023, https://doi.org/10.1002/
cpe.7581.
[16] P. F. Muhammad, R. Kusumaningrum, and A. Wibowo, “ScienceDirect ScienceDirect Sentiment Analysis Using Word2vec
And Long Short-Term Sentiment Analysis Using Word2vec And Long Short-Term Memory ( LSTM ) For Indonesian Hotel
Reviews Memory ( LSTM ) For Indonesian Hotel Reviews,†Procedia Computer Science, vol. 179, no. 2020, pp. 728–735,
2021, https://doi.org/10.1016/j.procs.2021.01.061.
[17] A. Sherstinsky, “Fundamentals of Recurrent Neural Network ( RNN ) and Long Short-Term Memory ( LSTM ) network,â€
Physica D, vol. 404, p. 132306, 2020, https://doi.org/10.1016/j.physd.2019.132306.
[18] T. Adewumi, F. Liwicki, and M. Liwicki, “Word2Vec : Optimal hyperparameters and their impact on natural language processing
downstream tasks,†pp. 134–141, 2022.
translation,†Applied Translation, pp. 10–17, 2021, https://doi.org/10.51708/apptrans.v15n1.1337.
[2] I. G. A. Budaya, M. W. A. Kesiman, and I. M. G. Sunarya, “Perancangan Mesin Translasi berbasis Neural dari Bahasa Kawi ke
dalam Bahasa Indonesia menggunakan Microframework Flask,†Jurnal Sistem dan Informatika (JSI), pp. 94–103, 2022.
[3] N. Rezaputra and Y. Denny, “Alih Bentuk Kalimat Non-Formal Menjadi Kalimat Formal Menggunakan Pendekatan Machine
Translation,†vol. 8, no. 1, pp. 379–390, 2022.
[4] N. Rezaputra and Y. D. Prabowo, “Alih Bentuk Kalimat Non-Formal Menjadi Kalimat Formal Menggunakan Pendekatan Machine
Translation,†KALBISIANA Jurnal Sains, Bisnis dan . . . , vol. 8, no. 1, pp. 379–390, 2020.
[5] J. C. Hsu, M. Wu, C. Kim, B. Vora, Y. T. Lien, A. Jindal, K. Yoshida, S. Kawakatsu, J. Gore, J. Y. Jin, C. Lu, B. Chen,
and B. Wu, “Applications of Advanced Natural Language Processing for Clinical Pharmacology,†Clinical Pharmacology and
Therapeutics, vol. 0, no. 0, pp. 1–9, 2024, https://doi.org/10.1002/cpt.3161.
[6] A. S. Talita and A.Wiguna, “Implementasi Algoritma Long Short-Term Memory (LSTM) UntukMendeteksi Ujaran Kebencian
(Hate Speech) Pada Kasus Pilpres 2019,†MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer, vol. 19,
no. 1, pp. 37–44, 2019, https://doi.org/10.30812/matrik.v19i1.495.
[7] Z. Abidin, “Statistical Machine Translation Pada Bahasa Lampung Dialek Api Ke Bahasa Indonesia,†vol. 4, pp. 519–528, 2020,
https://doi.org/10.30865/mib.v4i3.2116.
[8] Y. Fauziyah, R. Ilyas, and F. Kasyidi, “Mesin Penterjemah Bahasa Indonesia-Bahasa Sunda Menggunakan Recurrent Neural
Networks,†Jurnal Teknoinfo, vol. 16, no. 2, p. 313, 2022, https://doi.org/10.33365/jti.v16i2.1930.
[9] L. E. Haris and A. S. Pardiansyah, “Aplikasi Android Kamus Bahasa Indonesia-Sasak,†Jurnal Manajemen Informatika dan
Sistem Informasi, vol. 1, no. 1, p. 1, 2018, https://doi.org/10.36595/misi.v1i1.10.
[10] D. O. Sihombing, “Implementasi Natural Language Processing (NLP) dan Algoritma Cosine Similarity dalam Penilaian Ujian
Esai Otomatis,†Jurnal Sistem Komputer dan Informatika (JSON), vol. 4, no. 2, p. 396, 2022, https://doi.org/10.30865/json.v4i2.
5374.
[11] S. Yang, Y. Wang, and X. Chu, “A Survey of Deep Learning Techniques for Neural Machine Translation.â€
[12] R. A. J. Dabre, C. Chu, and A. Kunchukuttan, “99 A Survey of Multilingual Neural Machine Translation,†vol. 53, no. 5, 2020,
https://doi.org/10.1145/3406095.
[13] Z. Abidin, “Penerapan Neural Machine Translation untuk Eksperimen Penerjemahan secara Otomatis pada Bahasa Lampung
Indonesia,†Prosiding Seminar Nasional Metode Kuantitatif, no. 978, pp. 53–68, 2017.
[14] A. Burhanuddin, A. L. Qosim, and R. Amaliya, “Phrase Based and Neural Network Translation for Text Transliteration from
Arabic to Indonesia,†Matics, vol. 14, no. 1, pp. 13–17, 2022, https://doi.org/10.18860/mat.v14i1.13853.
[15] C. Avci, B. Tekinerdogan, and C. Catal, “Analyzing the performance of long short-term memory architectures for malware
detection models,†Concurrency and Computation: Practice and Experience, vol. 35, no. 6, p. 1, 2023, https://doi.org/10.1002/
cpe.7581.
[16] P. F. Muhammad, R. Kusumaningrum, and A. Wibowo, “ScienceDirect ScienceDirect Sentiment Analysis Using Word2vec
And Long Short-Term Sentiment Analysis Using Word2vec And Long Short-Term Memory ( LSTM ) For Indonesian Hotel
Reviews Memory ( LSTM ) For Indonesian Hotel Reviews,†Procedia Computer Science, vol. 179, no. 2020, pp. 728–735,
2021, https://doi.org/10.1016/j.procs.2021.01.061.
[17] A. Sherstinsky, “Fundamentals of Recurrent Neural Network ( RNN ) and Long Short-Term Memory ( LSTM ) network,â€
Physica D, vol. 404, p. 132306, 2020, https://doi.org/10.1016/j.physd.2019.132306.
[18] T. Adewumi, F. Liwicki, and M. Liwicki, “Word2Vec : Optimal hyperparameters and their impact on natural language processing
downstream tasks,†pp. 134–141, 2022.
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Published
2024-03-28
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How to Cite
[1]
H. Wardhana, I. M. Yadi Dharma, K. Marzuki, and I. Syarif Hidayatullah, “Implementation of Neural Machine Translation in Translating from Indonesian to Sasak Language”, MATRIK, vol. 23, no. 2, pp. 465–476, Mar. 2024, doi: 10.30812/matrik.v23i2.3465.
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