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Mustofa, Rifki, Mustofa, Arif 
ORCID: https://orcid.org/0000-0003-3480-8051 and Surur, Misbahus ORCID: https://orcid.org/0000-0002-9370-5004
(2025)
Variations of Arabic-Indonesian translation strategies in automatic machine translation: A comparative study.
Journal of Language and Literature Studies, 5 (3).
pp. 522-540.
ISSN 2808-1099
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Abstract
In the era of Society 5.0, the phenomenon of automatic translation is getting more attention as communication technology advances, especially with the presence of translation engines such as Auto Translation and ChatGPT. Both are widely used in language transfer, including for official texts such as diplomatic speeches. This study aims to identify and compare the translation strategies used by Auto Translation and ChatGPT in translating the Arabic speech delivered by Indonesian Deputy Foreign Minister Anis Matta during the OIC Summit in Riyadh on November 11, 2024. This research uses a descriptive qualitative approach with a comparative method. Primary data is obtained from Arabic speech transcripts and the results of the translation of the two machines, while secondary data comes from various relevant literatures. Data collection techniques were carried out through observation and note-taking, and analyzed using the Miles and Huberman model, which includes data reduction, data display, and conclusion drawing/verification. The results show that the most dominant strategy used by both is Transcription (34% Auto Translation, 42% ChatGPT). The Harfiyyah strategy was found 18% in Auto Translation and 19% in ChatGPT. The Ziyadah strategy appeared 12% in Auto Translation and 8% in ChatGPT. The Transposition strategy was found 6% in Auto Translation and 11% in ChatGPT. The Description strategy was used more by ChatGPT at 12% than Auto Translation with 3%). Taqdim wa ta'khir strategy appears equally at 6%, while Tabdil (9%) and Hazf (12%) strategies are only found in Auto Translation. The results show a significant difference in that Auto Translation is more flexible in replacing or omitting text elements, while ChatGPT is more descriptive and contextual. This research contributes to the study of technology-based translation, especially Arabic-Indonesian diplomatic texts.
| Item Type: | Journal Article |
|---|---|
| Keywords: | Anis Matta's speech; Arabic-Indonesian; Auto translation; ChatGPT; Translation strategy |
| Subjects: | 20 LANGUAGE, COMMUNICATION AND CULTURE > 2003 Language Studies > 200323 Translation and Interpretation Studies 20 LANGUAGE, COMMUNICATION AND CULTURE > 2004 Linguistics > 200409 Arabic Linguistics |
| Divisions: | Faculty of Humanities > Department of Arabic Language and Letters |
| Depositing User: | Misbahus Surur |
| Date Deposited: | 14 Oct 2025 09:40 |
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