Interlingual Translation Quality Via Artificial Intelligence
DOI:
https://doi.org/10.24090/celti.2025.1312Keywords:
Acehnese language, Artificial Intelligence, Bahasa, Interlingual, Machine TranslationAbstract
Artificial intelligence is so important to interlingual translation, nowadays. One of the translation machines that is currently trending among today's translation learners is a translation made by a giant company called Google with its product, Google Lens. Google Lens will help you translate interlingually using a smartphone connected to the internet and then in real time translate the text taken from the smartphone photo in the source language into the target language that is optionally selected according to the user's needs. this study examines the quality of interlingual translation using artificial intelligence from Google, known as Google Lens, which is capable of translating using a photography feature. This research is the quantitative which related to data measured with numerical symbols carried out using descriptive statistic. The conclusion is that the translation machine from the artificial intelligence-based translation machine by photographing Acehnese text into Indonesian needs to be further refined, especially to be more accurate, acceptable, and readable.
References
Abdullah, W., Faridan, A., Harun, M., Syafi’I, Hanum, F., Badruddin, & Husni, T. (2008). Peulajaran Basa AcehI: Keu Murip Glah VII SMP/MTsN. Geuci: Banda Aceh.
Alam, A. (2020). Google Translate Sebagai Alternatif Media Penerjemahan Teks Bahasa Asing Ke Dalam Bahasa Indonesia. Jurnal Instruksional, 1(2), 159-163.
Andriani, R. C. (2014). Tes Kebahasaan. Educate, 3(2), 21-29.
Andriani, R., Eriyanti, R. W., & Huda, A. M. (2023). Problem Dalam Menggunakan Mesin Terjemahan: Error Dalam Menterjemahkan Teks Bahasa Inggris ke dalam Bahasa Indonesia. INNOVATIVE: Journal Of Social Science Research, 3(3), 4385-4395.
Faridy, N., Bania, A. S., & Akob, B. (2025). Evaluating The Readability of Jawi To Latin Transliteration Via AI-Based Text Photography Applications. INJECT (Interdisciplinary Journal of Communication), 10(1), 115-132.
Miles, M.B. & Huberman, A.M. (2005). Qualitative Data Analysis (terjemahan). Jakarta, Indonesia: UI Press
Nababan, M, Nuraeni, A, & Sumardiono. (2012). Pengembangan Model Penilaian Kualitas Terjemahan. Kajian Linguistik dan Sastra, 24(1), 39-57.
Nurullawasepa, M., Mandani, N. Z., Adawiyah, R., Ayyubi, S. A., & Abdillah, A. A. (2023). AI (Artificial Intelligence) dalam penerjemahan teks Bahasa Arab. In: 3rdE-proceeding SENRIABDI 2023: Seminar Nasional Hasil Riset dan Pengabdian kepada Masyarakat (Surakarta), 3, 141-157.
Raissah, N., & Aziz, Z. A. (2020). An Investigation Of Interlingual And Ntralingual Interference Found In English As A Foreign Language (Efl) Students’ Composition Of Recount Text. English Education Journal, 11(2), 251-275.
Wedananta, K. A. (2017). Kesalahan Interlingual Dalam Bahasa Inggris Oleh Siswa Kelas Tujuh Smp Jembatan Budaya. Jurnal Ilmiah Manajemen dan Bisnis, 2(1), 71-79.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Allif Syahputra Bania, Mulyani, Fiza Rauzika Al Tasa, Najihatul Faridy, Nuraini, Bachtiar Akob, Teuku Hasan Basri

This work is licensed under a Creative Commons Attribution 4.0 International License.