Comparison of Google, Baidu, DeepL Chinese-Indonesian translations in AI Era

This study attempts to evaluate the quality of Chinese Indonesian machine translation offered by Google Translate, Baidu Translate, and DeepL in the context of the rapidly evolving artificial intelligence landscape. The study assesses the translation based on linguistic accuracy in terms of both syntactic and semantic approaches, using qualitative data from a sample set of 85 business language vocabularies commonly used in business usage concepts. The results reveal specific strengths and weaknesses. Google excels in overall accuracy and user accessibility; Baidu demonstrates a nuanced understanding of Mandarin cultural references, while DeepL offers improved fluency and naturalness. However, the overall translation score reveals several limitations in machine translation, particularly when it comes to translating standard vocabulary. This study emphasizes the need for machine translation system designs to bridge linguistic and cultural gaps. These findings provide significant insights for educators, translators, and developers who want to utilize AI-powered translation systems in multilingual communication.