Analisis Kualitas Terjemahan pada Aplikasi Deepl DeepL 应用中的翻译准确性分析 DeepL yìngyòng zhōng de fānyì zhǔnquè xìng fēnxī

Abstract

This research discusses the quality of the DeepL application translation of Mandarin-Indonesian folklore books. This research aims to identify the quality of translation results using the DeepL application and analyze errors. To analyze the errors that occurred, the author used Nababan's (2012) translation quality theory in the form of an accuracy rating instrument. The method used by the author is a qualitative descriptive method. The results of this research indicate that errors were found in the DeepL translation results. Furthermore, the DeepL translation lacks quality in terms of the choice of equivalent words (diction) and sentence structure. DeepL can only be used to search for one equivalent word from the source language to the target language. However, the equivalent of the words searched for are often very limited and not necessarily appropriate to the context of the sentence and cultural context. The conclusion is that DeepL is still just a machine that cannot match the abilities of humans who are equipped with detailed feelings and thinking.