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All Journal TEKNIK INFORMATIKA MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer IJISTECH (International Journal Of Information System & Technology) SENSITEK Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik Jurnal Bumigora Information Technology (BITe) Jurnal Teknimedia: Teknologi Informasi dan Multimedia IJISTECH Djtechno: Jurnal Teknologi Informasi ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Melek IT: Information Technology Journal International Journal of Electronics and Communications Systems Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Jurnal Ilmiah Pengabdian dan Inovasi Jurnal Riset Multidisiplin Edukasi Prosiding Seminar Nasional CORISINDO
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Universitas Bumigora
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Implementation of Neural Machine Translation in Translating from Indonesian to Sasak Language Helna Wardhana; I Made Yadi Dharma; Khairan Marzuki; Ibjan Syarif Hidayatullah
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3465

Abstract

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.
Co-Authors Abdurraghib Segaf Suweleh Affan, Usman Ibnu Andi Sofyan Anas Anthony Anggrawan Apriani Apriani Apriani Apriani Apriliana, Zikriati Arief Setyanto Arsa Wisesa, Gde Bagus Aryadita As’ary Ramadhan Asro Nasiri As’ary Ramadhan Ayu Dasriani, Ni Gusti azhar mardedi, lalu zazuli Azhar, Raisul Baiq Chandra Herawati Canggih Wahyu Rinaldi Dedy Febry Rachman Dewa Ayu Oki Astarini Dewi, Puspita Dyah Susilowati Dyah Susilowaty Eria Raudhatul Jannah Guterres, Juvinal Ximenes Hairani Hairani Hariyadi, I Putu Helna Wardhana Husain Husain Husain I Made Yadi Dharma I Putu Hariyadi Ibjan Syarif Hidayatullah Ikang Murapi Ikrom, Paizul Indah Puji Lestari Ismail Husein, Ismail Juliyanto, Fery Jusmita Weriza Khairul Imtihan Kholid, Muhammad Idham Kurniadin Abd Latif Lalau Ganda Rady Putra Lalu Ahmad Najmul Munir Lalu Ganda Rady Putra Lalu Zazuli AzharMardedi lauw, Christopher Michael Lilik Widyawati Lillik Widyawati M Fakhariza M Safii Mardedi, Lalu Zazuli Azhar Mardedi, Lalu Zazuli Azhar Maulana Ashari Maulid Putra Perdana Mia Mubiatma Mohammad Taufan Asri Zaen Muhammad Idham Kholid Naufal Hanif Naufal Hanif Ni Ketut Sriwinarti Noranizamardia Noranizamardia Ondi Asroni Parama Diptya Widayaka PUTRA, MUHAMAD ALVAN EKAWAN R. Ayu Ida Aryani Radimas Putra Muhammad Davi Labib Regina Pricilia Yunika Rifqi Hammad Sahimin, Sahimin Santoso, Heroe Sirojul Hadi Siti Soraya Sunardy Kasim Syamsurrijal, Syamsurrijal Tomi Tri Sujaka Usman Ibnu Affan Yudistira, Yudha Yusri Ikhwani Zakiyudin, Hizbu