User Trust Towards Google Translate in Translating Mandarin Idioms into Indonesian

As bilateral relations between Indonesia and China grow closer, demand for fast and reliable translation tools has increased, leading many people to rely on Google Translate and similar AI powered applications. However, frequent use does not always translate into full trust, as user confidence in these tools depends heavily on how reliable the translations are perceived to be. This study examines the relationship between AI reliability (the independent variable) and user trust (the dependent variable) using a quantitative explanatory design. Data were collected through a Likert-scale survey measuring perceptions of accuracy, consistency, and contextual appropriateness, alongside levels of trust in AI-generated translations. Participants were university students who had studied Mandarin for at least two years and had prior experience using Mandarin-Indonesian translation tools. Validity testing, reliability testing, descriptive statistics, and linear regression were used to examine the relationship between the two variables, followed by a focus group discussion (FGD) to provide deeper insight and validate the quantitative findings.Results show that user trust in Mandarin-Indonesian translation is significantly influenced by perceived AI reliability, with accuracy, consistency, and contextual appropriateness emerging as key contributors to trust formation. Notably, while users generally trust Google Translate, this trust does not always translate into full reliance many still verify translations, particularly those involving cultural content. This suggests that contextual accuracy plays a critical role in building user trust. Overall, precision in translating cultural expressions and idioms appears to matter more for building trust than fluency or naturalness of the output alone.