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Comparative Analysis of Arabic Translation Results Between ChatGPT and Deepl Annisa Fitria Allicia Jauhar; Agung Setiyawan
Tadris Al-'Arabiyyah: Jurnal Pendidikan Bahasa Arab dan Kebahasaaraban Vol. 4 No. 2 (2025): Tadris Al-'Arabiyyah: Jurnal Pendidikan Bahasa Arab dan Kebahasaaraban
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/ta.v4i2.46575

Abstract

The rapid advancement of artificial intelligence (AI) has significantly transformed translation studies, yet challenges persist in achieving semantic precision and syntactic fidelity in Arabic translation. While ChatGPT and DeepL are among the most widely used AI translation systems, comparative linguistic analyses of their Arabic translation performance remain underexplored. This study investigates both systems' morphological, syntactic, and semantic accuracy through a descriptive–comparative library research design. Data were drawn from Arabic academic texts in Qirā’ah al-Nuṣūṣ, analyzed using a back-translation technique and linguistic equivalence framework. The findings show that ChatGPT tends to generate more communicative and contextually adaptive outputs aligned with dynamic equivalence. In contrast, DeepL demonstrates more substantial formal and lexical precision consistent with formal equivalence principles. These results suggest that both systems offer complementary strengths that can enhance Arabic translation pedagogy and computational linguistics research. The study introduces a back-translation-based linguistic evaluation model that bridges Arabic linguistic complexity with computational precision, filling a notable gap in AI-assisted Arabic translation research.  
Unraveling Linguistic and Extralinguistic Barriers in Understanding Istimāʿ al-Akhbār Oktavia Dwi Lestari; Agung Setiyawan; Dudung Hamdun; Suci Noor Asa Khaliza; Salsa Hauna Ajidin
Al-Wazan: Journal of Arabic Education Vol. 4 No. 2 (2026)
Publisher : Sekolah Tinggi Agama Islam Darul Ulum Banyuanyar Pamekasan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58223/al-wazan.v4i2.968

Abstract

Students often face difficulties in comprehending authentic Arabic news due to the interaction of linguistic and extralinguistic barriers, yet research specifically examining these challenges remains limited. This study aims to explore the linguistic and extralinguistic barriers experienced by students in understanding istimāʿ al-akhbār (Arabic news listening) and to identify the strategies they employ to overcome these difficulties. A qualitative approach with a descriptive-exploratory design was adopted, involving 37 students from the Arabic Language Education Program at UIN Sunan Kalijaga Yogyakarta. Data were collected through an open-ended questionnaire administered via Google Forms and analyzed using qualitative content analysis through coding, categorization, and thematic identification. The findings indicate that linguistic barriers were dominant, particularly limited vocabulary mastery and broadcasters’ rapid speech rate, each occurring 23 times. Other linguistic barriers included unfamiliar news terminology and pronunciation difficulties. Extralinguistic barriers included lack of concentration, limited prior knowledge, fatigue, low interest, low motivation, and anxiety. Students addressed these challenges by replaying recordings, noting vocabulary, and translating unfamiliar expressions. This study contributes a comprehensive understanding of the interaction between linguistic and extralinguistic barriers and highlights the importance of thematic vocabulary development, prior-knowledge activation, and systematic listening-strategy training.