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All Journal Aphorisme: Journal of Arabic Language, Literature, and Education Tadris al-'Arabiyyah: Jurnal Pendidikan Bahasa Arab dan Kebahasaaraban
Jauhar, Annisa Fitria Allicia
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Religion Arts Humanities Education Languange, Linguistic, Communication & Media Other

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Pendekatan Ilmu Ma‘ani terhadap Struktur Kalam dan Makna Tersirat dalam Surah Yusuf Jauhar, Annisa Fitria Allicia
Aphorisme: Journal of Arabic Language, Literature, and Education Vol. 6 No. 1 (2025): Arabic Language, Literature, and Education
Publisher : Study Program of Arabic Language Teaching

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37680/aphorisme.v6i1.7410

Abstract

This study explores the application of ilmu ma‘ani elements, such as kalam khabar, kalam insya’, qaṣr, al-faṣl wa al-waṣl, ījāz, iṭnāb, and Musāwah in selected verses of Surah Yusuf to uncover their rhetorical functions and implicit spiritual messages. This research employs a qualitative method with a library research design, focusing on linguistic structures and rhetorical expressions within the Qur’anic text. Primary data consists of verses from Surah Yusuf. In contrast, secondary data is derived from classical and contemporary tafsir (e.g., Tafsir Ibn Kathir, Tafsir al-Jalalayn, Tafsir al-Tahrir wa al-Tanwir) and relevant scholarly articles. Data were collected using documentation techniques and analyzed through content analysis, identifying rhetorical forms and interpreting their implied meanings through a balaghah framework. The findings conclude that the meticulous use of ilmu ma‘ani in Surah Yusuf exemplifies the Qur'an's linguistic miracle, where concise yet rich language effectively and efficiently delivers intricate spiritual and ethical messages, affirming its timeless relevance.
Comparative Analysis of Arabic Translation Results Between ChatGPT and Deepl Jauhar, Annisa Fitria Allicia; Setiyawan, Agung
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.  
Co-Authors Agung Setiyawan, Agung