Artificial Intelligence in Arabic-Malay Qur’an Translation: Potentials, Limits, and Scholarly Oversight

Muhammad Muthi'ul Haqq Fatah Yasin, Mohamad Dhiya’ul Hafidh Fatah Yasin, Syahraini Tambak, Raudlotul Firdaus Fatah Yasin, Wafa Abdul Jabbar Shohibuddin

Abstract


This article examines the role of artificial intelligence (AI) in the translation of the Qur’an from Arabic into Malay. The topic is important because Qur’anic translation involves not only lexical transfer, but also rhetorical force, theological precision, and sensitivity to Malay Islamic usage. Using a qualitative document analysis approach, this study reviews recent scholarship on Qur’anic translation, AI-assisted translation, Arabic natural language processing, and Arabic language learning published mainly between 2020 and 2026. The analysis shows that AI can support translators in several ways, especially by accelerating draft production, improving lexical consistency, and assisting the comparison of alternative renderings across large textual corpora. However, the literature also demonstrates persistent weaknesses in handling near-synonymy, polysemy, legal verses, figurative language, and context-bound theological meanings. For the Arabic-Malay pair, these weaknesses become more pronounced because translation quality depends on both Arabic semantic depth and the established exegetical style of Malay Islamic discourse. The article argues that AI should be positioned as an assistive instrument rather than an autonomous translator of the Qur’an. A hybrid workflow is therefore proposed, combining AI-generated drafts with tafsir-based validation, terminology control, and expert human post-editing. The study contributes a focused synthesis for Arabic-Malay translation studies and offers practical implications for Arabic learning, translator training, and future corpus development.


Keywords


Qur’an; Translation; Arabic-Malay; Artificial Intelligence; Neural Machine Translation; Tafsir-Informed Translation

References


(COPE), C. on P. E. (2023). Authorship and AI tools. COPE.

(OECD), O. for E. C. and D. (n.d.). AI Principles. OECD.

(UNESCO), U. N. E. S. and C. O. (2021). Recommendation on the Ethics of Artificial Intelligence. UNESCO.

Abdalhussein, H. F. (2025). Comparative Analysis Of AI And Human Translations Of Qur’anic Legal Verses In Surah Al-Ma’idah. Ijaz Arabi Journal of Arabic Learning, 8(1), 262–277. https://doi.org/10.18860/ijazarabi.v8i1.28804

Abdul-ghafour, A. K., Aladdin, A., Zainudin, I. S., & Awal, N. M. (2022). Contextual Meanings Of Qur’ānic Near-Synonyms And Their Translations. Ijaz Arabi: Journal of Arabic Learning, 5(3), 796–811. https://doi.org/https://doi.org/10.18860/ijazarabi.v5i3.16519

Abou Adel, M. (2022). Investing Artificial Intelligence For Arabic Learning. Ijaz Arabi: Journal of Arabic Learning, 5(1), 234–248. https://doi.org/https://doi.org/10.18860/ijazarabi.v5i1.15814

Al-Shaboul, I. A., Ali, A. A., Kariem, A. I. A., Zarovna, I., Glushchenko, T., & Khasawneh, M. A. S. (2025). Bridging the gap: The role of artificial intelligence in enhancing Arabic language learning, translation, and speech recognition. Research Journal in Advanced Humanities, 6(2).

Al Farisi, M. Z. (2023). ACCEPTABILITY OF THE QURAN TRANSLATION. Al-Jāmi‘ah: Journal of Islamic Studies, 61(2), 329–363. https://doi.org/10.14421/ajis.2023.612.329-363

Albalawi, A. F. (2025). Bringing Meanings : AI And Human Collaboration in Unveiling Qur ’ anic Synonymy and Polysemy. Ijaz Arabi Journal of Arabic Learning, 8(1), 155–168. https://doi.org/https://doi.org/10.18860/ijazarabi.v8i1.29910

Albalawi, A. F., & Abdul-ghafour, A. K. (2024). Unravelling Qur ’ anic Puns through AI English Translation. Ijaz Arabi Journal of Arabic Learning, 7(2), 680–695.

Alduhaim, A. (2021). Translating Near-Synonyms in the Quran : A Semantic Analysis of Three Near- Synonyms and their English Translations. The Southeast Asian Journal of English Language Studies, 27(1), 76–89. https://doi.org/https://doi.org/10.17576/3L-2021-2701-06

Ariffin, A., & Mansor, I. (2022). Constraints in translating the style of Quran into Malay. Journal of Language and Linguistic Studies, 18(1), 1124–1134.

Baihaqi, M., Syarifah, A., & Arif, M. (2025). Enhancing Arabic Translation Competency In Higher Education: An Evaluation Of The Becoming A Translation Practitioner’ Program. Ijaz Arabi: Journal of Arabic Learning, 8(1), 493–503. https://doi.org/https://doi.org/10.18860/ijazarabi.v8i1.31642

Borham, S. R., Ramli, S., Taufiq, M., & Ghani, A. (2024). AI Concepts Integration in Developing E-Muhadathat Kits For Non-Arabic Speakers. Ijaz Arabi: Journal of Arabic Learning, 7(3), 1215–1225. https://doi.org/https://doi.org/10.18860/ijazarabi.v7i3.26568

Boulaouali, T. (2021). Quran translation: A historical-theological exploration. International Journal of Islamic Thought, 19(1), 120–132. https://doi.org/10.24035/IJIT.19.2021.202

Callison-Burch, C., Osborne, M., & Koehn, P. (2006). Re-evaluating the Role of B LEU in Machine Translation Research. In D. McCarthy & S. Wintner (Eds.), 11th Conference of the European Chapter of the Association for Computational Linguistics (pp. 249–256). Association for Computational Linguistics.

Freitag, M., Foster, G., Grangier, D., Ratnakar, V., Tan, Q., & Macherey, W. (2021). Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation. In B. Roark & A. Nenkova (Eds.), Transactions of the Association for Computational Linguistics, Volume 9 (pp. 1460–1474). MIT Press. https://doi.org/10.1162/tacl_a_00437

Gaanoun, K., & Alsuhaibani, M. (2025). Sentiment preservation in Quran translation with artificial intelligence approach: study in reputable English translation of the Quran. Humanities and Social Sciences Communications, 12(1), 1–15. https://doi.org/10.1057/s41599-024-04181-0

Haroun, Y. (2025). The Essential Role of Arabic Linguistics and Etymology in Qur’anic Translation. Journal of Islamic and Muslim Studies, 10(1), 106–121.

Kamarudin, M. A., Zailani, S., Kamarzaman, M. H., & Zakarim, M. Z. M. (2026). Thematic Structure of Rhetorical Imperative Sentences in the Quran as Arabic Literature and Its Translation into Malay. Ijaz Arabi: Journal of Arabic Learning, 9(1), 101–116. https://doi.org/https://doi.org/10.18860/ijazarabi.v9i1.35329

Khair, M. M., & Sawalha, M. (2025). Automated Translation of Islamic Literature Using Large Language Models: Al-Shamela Library Application. Proceedings - International Conference on Computational Linguistics, COLING, 53–58.

Khan, L. F. (2020). Challenges in Machine Translation For Teaching Arabic Language. Ijaz Arabi: Journal of Arabic Learning, 3(2), 264–273. https://doi.org/10.18860/ijazarabi.v3i2.10063

Koehn, P., & Germann, U. (2014). The Impact of Machine Translation Quality on Human Post-Editing. In U. Germann, M. Carl, P. Koehn, G. Sanchis-Trilles, F. Casacuberta, R. Hill, & S. O’Brien (Eds.), Proceedings of the EACL 2014 Workshop on Humans and Computer-assisted Translation (pp. 38–46). Association for Computational Linguistics.

Kudo, T., & Richardson, J. (2018). SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing. In E. Blanco & W. Lu (Eds.), Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations (pp. 66–71). Association for Computational Linguistics. https://doi.org/10.18653/v1/D18-2012

Licht, D., Gao, C., Lam, J., Guzman, F., Diab, M., & Koehn, P. (2022). Consistent Human Evaluation of Machine Translation across Language Pairs. In K. Duh & F. Guzmán (Eds.), Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Vol. 1, pp. 309–321). Association for Machine Translation in the Americas.

Mohd Saad, M. L. I. H., Ab. Halim, Z., Rouyan, N. M., & Zakaria, R. (2024). AMBIGUITY IN THE TRANSLATION OF QURANIC EUPHEMISMS INTO THE MALAY LANGUAGE. Journal of Nusantara Studies, 9(1), 74–96. https://doi.org/https://doi.org/10.24200/jonus.vol9iss1pp74-96

Mohd Saad, M. L. I. H., & Rouyan, N. M. (2024). Impak Pendekatan Terjemahan Terhadap Kualiti Penterjemahan Eufemisme al-Quran ke Bahasa Melayu. Global Journal Al-Thaqafah, 14(1), 80–96. https://doi.org/https://doi.org/10.7187/GJAT072024-6

Mubarak, F., Rahman, A. A., Althobaiti, N. A. A., & Deviana, A. D. (2025). Development Of Indonesian-Arabic Language Translation Teaching Strategies With Cultural Understanding. Ijaz Arabi: Journal of Arabic Learning, 8(3), 1516–1525. https://doi.org/https://doi.org/10.18860/ijazarabi.v8i3.10128

Othman, A. M. W., & Asbulah, L. H. binti. (2025). Problems Of Artificial Intelligence Applications In Digitizing The Arabic Language In The Areas Of Grammar And Morphology And Methods To Resolve It. Ijaz Arabi: Journal of Arabic Learning, 8(2), 721–740. https://doi.org/https://doi.org/10.18860/ijazarabi.v8i2.31596

Ott, M., Edunov, S., Baevski, A., Fan, A., Gross, S., Ng, N., Grangier, D., & Auli, M. (2019). fairseq: A Fast, Extensible Toolkit for Sequence Modeling. In W. Ammar, A. Louis, & N. Mostafazadeh (Eds.), Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations) (pp. 48–53). Association for Computational Linguistics. https://doi.org/10.18653/v1/N19-4009

Sumiarni, N., Saefuloh, H., Pratama, M. I., & Setiawan. (2026). Transforming Arabic Language Learning With Artificial Intelligence : Teacher Perspectives And Student Experiences. Ijaz Arabi: Journal of Arabic Learning, 9(1), 237–252. https://doi.org/https://doi.org/10.18860/ijazarabi.v9i1.35113

Van der Lee, C. van der, Gatt, A., Miltenburg, E. van, Wubben, S., & Krahmer, E. (2019). Best practices for the human evaluation of automatically generated text. In K. van Deemter, C. Lin, & H. Takamura (Eds.), Proceedings of the 12th International Conference on Natural Language Generation (Issue 2015, pp. 355–368). Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-8643

Wieting, J., Berg-Kirkpatrick, T., Gimpel, K., & Neubig, G. (2019). Beyond BLEU: Training Neural Machine Translation with Semantic Similarity. In A. Korhonen, D. Traum, & L. Màrquez (Eds.), Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (pp. 4344–4355). Association for Computational Linguistics. https://doi.org/10.18653/v1/P19-1427




DOI: https://doi.org/10.18860/ijazarabi.v9i4.42119

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Copyright (c) 2026 Muhammad Muthi'ul Haqq Fatah Yasin, Mohamad Dhiya’ul Hafidh Fatah Yasin, Syahraini Tambak, Raudlotul Firdaus Fatah Yasin, Wafa Abdul Jabbar Shohibuddin

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