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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Proceedings of KNASTIK TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Informatika Jurnal Sarjana Teknik Informatika Rekursif: Jurnal Informatika Jurnas Nasional Teknologi dan Sistem Informasi Komuniti : Jurnal Komunikasi dan Teknologi Informasi EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Mobile and Forensics Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) ABDIMASTEK
Dewi Soyusiawaty
Universitas Ahmad Dahlan
Aerospace Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Neuroscience Social Sciences

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Journal : Building of Informatics, Technology and Science

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Optimasi Kombinasi Hyperparameter dan Augmentasi Korpus dalam Neural Machine Translation Bahasa Indonesia ke Bahasa Melayu Bengkulu Soyusiawaty, Dewi
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5369

Abstract

Neural Machine Translation (NMT) with attention mechanism has become an effective approach in improving the quality of cross-language translation. However, the application of NMT with attention to regional or minority languages still faces challenges, especially in the context of Bengkulu Malay Language, a variant of Malay Language used in the Bengkulu Province, Indonesia. This research aims to enhance the translation accuracy from Indonesian to Bengkulu Malay Language through optimization of hyperparameter combinations in NMT models with attention. The research method involves experiments with various hyperparameter combinations, such as batch size, dataset size, and dropout rate, applied to NMT models with attention. Evaluation is conducted using the BLEU metric to measure translation quality. Corpus augmentation is done to obtain a larger corpus.The experimental results indicate that translation accuracy improvement can be achieved by selecting optimal hyperparameter combinations. The use of a larger dataset yields better performance compared to a smaller dataset. A batch size of 16 yields better results than batch sizes of 32 and 64, especially when used with a larger dataset. Additionally, a dropout rate of 0.8 tends to perform better than dropout rates of 0.2 and 0.5. Regarding epoch values, the research shows that increasing epochs up to a certain point (approximately 30 epochs) enhances model performance, but further increases tend to cause overfitting on the training data. This research provides a significant contribution to the development of machine translation for Bengkulu Malay Language and other regional languages. It is hoped that the findings of this research can serve as a foundation for further development in the field of machine translation for minority languages, as well as improving information accessibility in diverse language communities in Indonesia.
Co-Authors Abdul Fadlil Aldini Fujiarti Aning Setiya Rini Ardian M.N. Buhari Muslim Catur Prasongko Devi Ayunani Wandasari Endri Rahmawanto Enggar Tyasto Wingwirawan Esty Istiqamah Failasuf Abid Dainuri Fathurrahman Fathurrahman Freddy Alpino Furqon, Ihtiar Nur Hapsari, Intan Herman Yuliansyah, Herman Irfan Nur Aditya Jones, Anna Hendri Soleliza Kholid Rohman Saputro Linda Mariana Lisna Zahrotun Muhammad Kunta Biddinika Nizar Anggit Pramana Nuri Piyanto Perdana, Tirtanusa Kurnia Adhi Ramadhan, Imam Razak, Farhan Radhiansyah Rosary Indah Dewi Sunardi Sunardi