Google Translate Mengubah Bahasa Batak Menjadi Bahasa Indonesia
DOI:
https://doi.org/10.62951/repeater.v3i2.399Keywords:
Artificial Intelligence, Automatic Translation, Batak Language, Neural Machine TranslationAbstract
Google Translate is an artificial intelligence-based translation service developed by Google. Since its introduction in 2006, this service has continued to create with the application of Neural Machine Translation (NMT) technology, which improves the accuracy and fluency of translation compared to previous methods. This study aims to determine the effectiveness and limitations of Google Translate in translating Batak into Indonesian. The research method used is descriptive qualitative with a comparative approach of Google Translate translation results and manual translations by professional translators. The study results show that Google Translate can translate basic words and simple sentences quite well. However, there are several limitations, such as a lack of understanding of the cultural context, idioms, and dialect variations in the Batak language. In addition, the translation is also influenced by the limitations of the database and vocabulary enrichment in this service. Thus, although Google Translate can be a tool in translation, users still need to do manual verification to ensure accuracy, especially in fields that require high precision such as law, academics, and professional communication.
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References
Amka. (2017). Implementasi pendidikan karakter inklusif bagi anak berkebutuhan khusus di sekolah reguler. Jurnal Disabilitas, 1(1), 1-9.
Borman, R. I. (2019). Klasifikasi objek kode tangan pada pengenalan isyarat alphabet bahasa isyarat Indonesia (BISINDO). Seminar Nasional Informatika dan Aplikasinya.
Borman, R. I., & Priyopradono, B. (2018). Implementasi penerjemah bahasa isyarat pada bahasa isyarat Indonesia (BISINDO) dengan metode principal component analysis (PCA). Jurnal Pengembangan IT, 3(1), 103–108.
Google Inc. (2024). Google Translate: A tool for bridging language barriers. Retrieved from https://translate.google.com
Hall, M., & Richards, S. (2020). Challenges and advancements in online translation tools: A comparison of Google Translate and competitors. International Journal of Language Studies, 12(4), 22-38.
Irawan, H., Fonda, Y., & Febriani, A. (2020). Klasifikasi batik Riau dengan menggunakan convolutional neural networks (CNN). Jurnal Ilmu Komputer, 9(1), 8-10. https://doi.org/10.33060/JIK/2020/Vol9.Iss1.144
Khesya, N. (2021). Mengenal flowchart dan pseudocode dalam algoritma dan pemrograman. OSF Preprints, 7-15. https://doi.org/10.31219/osf.io/dq45e
Kumar, S., & Patel, R. (2021). The role of AI in language translation: Exploring Google Translate's features. Springer.
Makahaube, S., Sambul, A. M., & Sompie, S. R. U. A. (2021). Implementation of gesture recognition technology for automated education service kiosk. Jurnal Teknik Informatika, 16(4), 465-472. https://doi.org/10.35793/jti.16.4.2021.34210
Misri, A. (2011). Aplikasi penterjemah untuk bahasa Indonesia ke bahasa Cirebon dan sebaliknya. Skripsi Teknik Informatika UAD.
Muharram, R. F. (2021). Implementasi artificial intelligence untuk deteksi masker secara realtime dengan tensorflow dan ssd mobilenet berbasis python. JRKT (Jurnal Rekayasa Komputasi Terapan), 1(3), 139-146.
Mursita, R. A. (2019). Respon tunatungu terhadap penggunaan sistem bahasa isyarat Indonesia (SIBI) dan bahasa isyarat Indonesia (BISINDO). INKLUSI Journal of Disability Studies, 2, 221-232.
Nguyen, T., & Tran, H. (2023). The impact of artificial intelligence on language translation: A case study of Google Translate. Journal of Language Technology, 18(3), 45-59. https://www.tandfonline.com/doi/full/10.1080/14790718.2023.2224013#abstract
Rahmadewi, R., Purwanti, E., & Efelina, V. (2018). Identifikasi jenis tumbuhan menggunakan citra daun berbasis jaringan saraf tiruan (artificial neural networks). Jurnal Media Elektro, 38-43.
Rasjid, F. E. (2019). Android-sistem-operasi-pada-smartphone. Retrieved from https://sim.ubaya.ac.id/android-sistem-operasi-pada-smartphone [March 26, 2022]
Rinaldi, R. (2019). Penerapan unified modelling language (UML) dalam analisis dan perancangan aplikasi e-learning Simtika. Jurnal Sistem Informasi, 2(1), 43–50.
Saputri, N. A. O., & Huda, N. (2018). Aplikasi pembelajaran bahasa isyarat bagi penyandang disabilitas tunarungu berbasis desktop. JUSIFO (Jurnal Sistem Informasi), 77-88. https://doi.org/10.31219/osf.io/dq45e
Saputro, K. E. (2019). Analisis dan perancangan kamus interaktif bahasa isyarat Indonesia dengan speech recognition. Jurnal Sistem Informasi, 1(2), 110-115.
Tjahyanti, L. P. A. S., & Setiawan, G. D. (2019). Perancangan media pembelajaran bahasa isyarat merangkai kalimat penyandang disabilitas anak tunarungu wicara berbasis web. DAIWI WIDYA Jurnal Pendidikan, 6(3), 44-57.
Wikipedia. (n.d.). Bahasa Rejang. Retrieved from http://id.wikipedia.org/wiki/Bahasa_Rejang
Zhang, L., & Li, W. (2022). Machine translation and AI: The evolution of Google Translate. Oxford University Press.
Zul, M. I. (2018). Feature extraction for hand shape recognition by using IP camera. Regional Conference on Computer and Information Engineering.
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