ANALYSIS OF TRANSLATION ERRORS IN GOOGLE TRANSLATE ARABIC TEXTS INTO INDONESIAN IN THE BOOK IHYA' ULUMUDDIN
DOI:
https://doi.org/10.30739/tarbiyatuna.v6i2.4965Keywords:
Error Analysis, Google Translate, Ihya' Ulumuddin BookAbstract
This research aims to identify the errors of Google Translate in translating Arabic text into Indonesian in the book Ihya' Ulumudin, specifically in the fields of syntax and semantics. The type of research used in this study is library research, which is a data collection technique involving a review of books related to the problem to be solved. The data used in this study is from the book "Ihya' 'Ulumuddin" volume 3, chapter "Al-Riya'u Al-Khafi" which is more hidden than the crawling of ants. Data analysis in this study was done by collecting data, recording errors, describing errors, and evaluating errors. The results of this study are that Google Translate still has many shortcomings in translating Arabic text into Indonesian, especially for yellow book texts which are heavily laden with nahwu and shorof rules. As for the errors in Google Translate in the field of syntax found in this study, they are: errors in translating superlative verbs, errors in translating plural sentences, errors in translation, errors in translating compound structures, and errors in Google Translate's translation of passive participles. Google's semantic errors include: mistranslation of the same letters with different vowel marks, incorrect word choice, inaccurate translation of hidden pronouns, Google's error in translating the letter qod, grammatical errors, and errors in translating the benefits of letters. The implications of this research indicate that the use of Google Translate as a tool for translating Arabic religious texts, particularly classical texts, needs to be accompanied by adequate linguistic understanding. These findings can also serve as a reference for teachers, students, and Arabic translators to be more critical in using translation machines and to encourage the development of translation technology that is more sensitive to the syntactic structure and semantic meaning of classical Arabic.
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