<![CDATA[Academic achievement is the most important part of every student's learning process, so it is important to identify various factors that influence it. Therefore, this study aims to: 1) analyze the effect of academic stress and academic burnout on AI-motivation learning?, 2) analyze the effect of academic stress, academic burnout and AI-motivation learning on academic achievement?, 3) analyze the effect of academic stress and academic burnout on academic achievement through AI-motivation learning?. This study uses a quantitative approach with a cross-sectional study design. The research location is ISBI Singkawang with a population of 578, then a sample of 236 was taken using a simple random sampling technique. The data collection technique used is measurement with a psychological scale instrument adopted from previous studies. Data analysis techniques use percentages, correlations, multivariate analysis, and linear regression analysis with a path analysis approach. The results of the study show that: 1) academic stress (β = −.403) and academic burnout (β = −.545) have a significant effect on AI-motivation learning, 2) academic burnout (β = −.400) and AI-motivation learning (β = .491) significantly influence academic achievement. 3) AI-motivation learning can mediate the relationship between academic stress and academic achievement (β = -.198). This finding has implications for the development of programs in University related to optimizing the use of AI in the learning process to increase student learning motivation.]]>
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