Investigating Semantic Errors in English to Indonesian Translations: A Case Study of DeepL Translator

This study focuses on investigating semantic errors in English to Indonesian translation using DeepL Translate, with the aim of evaluating the extent of semantic accuracy of this translation tool. This study uses a qualitative approach with a case study design, where data is collected by observing translations during a conversation between a native English speaker and a native Indonesian speaker. Each translation was analysed using a qualitative descriptive method to identify semantic errors, which were classified into three categories: inappropriate word choice, loss of implicit meaning, and ambiguity of sentence structure. The results showed that out of 50 translated sentences, there were 15 semantic errors, with inappropriate word choice being the dominant category. The conclusion of this study is that while DeepL is capable of producing relatively good translations, its limitations in understanding semantic context remain a significant bottleneck. The study recommends further development of the automatic translation algorithm and training of users to use the technology critically and judiciously. Keywords: deepL translate, english to indonesian translation, semantic errors