Kualitas Terjemahan Artificial Intelligence: Studi Komparatif Keberterimaan Terjemahan Deepseek AI dan Claude AI pada Teks Akademik Berbahasa Arab
Contributors
Akhmad Saehudin
Adira Syahputri
Anjani Aulia Maharani
Dinda Julia
Keywords
Proceeding
Track
General Track
License
Copyright (c) 2025 International Conference on Cultures & Languages

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Abstract
This study aims to test the quality of Artificial Intelligence translation by comparing the translation results of DeepSeek AI and Claude AI on Arabic academic texts. The selected academic document is an abstract text as the core of a scientific work that concisely explains the main topic, purpose or focus, methods, main findings, and conclusions. This research uses a qualitative descriptive approach with the data corpus sourced from the International Journal for Scientific Research entitled “الفرق بين معاني مترادف القرآن الكريم بين المعانين والغالين” by Abdul Mohsen Zaben Mutab al-Matiri and Mujahid Mustafa Bahjat. The theory used in this study is Mangatur Nababan's translation quality theory. The results of this study show that DeepSeek AI is superior in translating Arabic scientific terms into Indonesian with an acceptability rate of 2.8 compared to Claude AI which has an acceptability rate of 2.2. This study contributes to showing how well artificial intelligence, especially Claude AI and DeepSeek AI can produce translations of academic texts that are acceptable to the target audience, with strict scientific language standards