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All Journal Al-Ta'rib : Jurnal Ilmiah Program Studi Pendidikan Bahasa Arab UIN Palangka Raya Thariqah Ilmiah ; Jurnal ilmu-ilmu kependidikan & Bahasa Arab
M. Zacky Mubarok
Universitas Islam Negeri Syarif Hidayatullah Jakarta
Religion Humanities Education Languange, Linguistic, Communication & Media Social Sciences Other

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ANALYSIS OF POLITICAL-CULTURAL TERM TRANSLATION TECHNIQUES IN AL-MAYADEEN NEWS: USING GROK AI Ariqah Nurussalwa; M. Zacky Mubarok; Muhammad Anas; Darsita Suparno
Thariqah Ilmiah: Jurnal ilmu-ilmu kependidikan & Bahasa Arab Vol 14, No 1 (2026): THARIQAH ILMIAH: JURNAL ILMU-ILMU KEPENDIDIKAN & BAHASA ARAB
Publisher : Universitas Islam Negeri Syekh Ali Hasan Ahmad Addary Padangsidimpuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24952/thariqahilmiah.v14i1.19947

Abstract

This study examines Grok AI's translation of Arabic political-cultural terms into Indonesian in Al-Mayadeen news texts. The topic is important because political news translation negotiates cultural meanings, ideology, and political perspectives that may influence readers. Five Arabic-language Al-Mayadeen news articles about Hamas from January to December 2024 were used to extract political-cultural terms for descriptive qualitative translation studies. The analysis classifies micro-level translation techniques using Molina and Albir's framework. Literal translation, borrowing, and established equivalence are Grok AI's most common translation methods, along with modulation, transposition, amplification, generalization, adaptation, and reduction. While these methods improve readability, they also change nuance and ideology, especially in reduction and generalization. This study shows that Grok AI can support political news translation, but human critical evaluation is still needed to ensure cultural sensitivity, ideological accuracy, and contextual integrity.
Measuring the Technique and Quality of Instagram Caption Auto-Translation to Improve @alarabiya Account Translation Results Gelsya Serinastity; M. Zacky Mubarok; Akhmad Saehudin; Darsita Suparno; Fathalah Mohamed Fathalah
AL-TA'RIB : Jurnal Ilmiah Program Studi Pendidikan Bahasa Arab IAIN Palangka Raya Vol 13 No 2 (2025)
Publisher : Universitas Islam Negeri Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23971/altarib.v13i2.10410

Abstract

The increasing use of machine translation (MT) on social media poses challenges for cross-linguistic and cross-cultural understanding, as these systems often fail to capture contextual meaning and cultural nuances. This study analyzes the techniques and quality of MT in social media content, an area with limited prior research. Using a qualitative-descriptive method, the study evaluates captions from Instagram @alarabiya by applying Molina & Albir's (2002) translation technique theory and Nababan's (2012) translation quality assessment scale. Analysis of 18 data samples revealed the dominance of the literal translation technique (27.27%). The quality assessment yielded average scores below the 'adequate' category in readability (μ=2.24), acceptability (μ=2.43), and accuracy (μ=2.50) on a 1-5 scale. These findings confirm the limitations of MT in processing informative texts rich in cultural context, resulting in outputs that tend to be difficult to understand, less acceptable, and inaccurate. This study highlights the urgency of enhancing cultural sensitivity in MT development and the importance of user literacy in critically engaging with automated translation outputs on digital platforms.
Co-Authors Ariqah Nurussalwa Darsita Suparno Fathalah Mohamed Fathalah Gelsya Serinastity Muhammad Anas Saehudin, Akhmad