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All Journal Journal of Arabic Language and Literature Studies
Nailis Saniyyah
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Arts Languange, Linguistic, Communication & Media

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THE CHALLENGE OF TRANSLATING ARABIC IN THE DIGITAL AGE: TESTING THE ACCURACY OF CONVENTIONAL TRANSLATION VERSUS ARTIFICIAL INTELLIGENCE: TANTANGAN PENERJEMAHAN BAHASA ARAB DI ERA DIGITAL: MENGUJI AKURASI TERJEMAHAN KONVENSIONAL VERSUS ARTIFICIAL INTELLIGENCE Hifni, Ahmad; Nova Klarisa; Nailis Saniyyah
Journal of Arabic Language and Literature (ALLAIS) Vol. 4 No. 2 (2025)
Publisher : Universitas Islam Negeri Raden Mas Said Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22515/allais.v4i2.12625

Abstract

This study compares the accuracy and quality of Arabic-to-Indonesian administrative document translation through two approaches: conventional (manual) translation using an Arabic dictionary and automated translation using Artificial Intelligence. The research employed a qualitative descriptive method with a comparative case study design, focusing on a Bachelor's Degree Certificate in Journalism from Akhbar Elyom Academy, Egypt (2017). The data corpus consists of the original Arabic version of the certificate and two translated versions: one produced through conventional translation and the other generated by ChatGPT. Analysis was conducted side by side, emphasizing semantic accuracy, lexical equivalence, and textual readability. The theoretical framework draws upon the equivalence concepts of Eugene Nida and Peter Newmark, as well as diction evaluation principles proposed by Gorys Keraf. The findings indicate that conventional (manual) translation performs better, particularly in terms of denotative and lexical accuracy, while ChatGPT translation tends to excel in readability, contextual appropriateness, and the use of more common diction. This study recommends a hybrid approach that integrates the strengths of traditional Arabic dictionaries with advancements in artificial intelligence to enhance the quality of Arabic-to-Indonesian translation.
Co-Authors Hifni, Ahmad Nova Klarisa