This study aims to examine how the application of a machine learning-based learning system to students' learning psychology. This study focuses on improving the quality of learning that not only pays attention to cognitive aspects, but also to students' emotional aspects that often affect their academic achievement. This study uses a qualitative approach with a descriptive research type to explore students' experiences in using a machine learning-based system in the learning process. Data collection techniques are carried out through interviews, observations, and documentation, with data analysis using the Miles and Huberman model. The results of the study indicate that the application of this system is effective in reducing academic anxiety (Academic Anxiety Reduction), increasing students' self-confidence through positive reinforcement (Increased self-confidence through positive reinforcement), and developing students' emotional resilience (Positive Resilience to Emotional Learning). The contribution of this study is to provide new insights into the role of technology, especially machine learning, in supporting the development of students' emotional intelligence which can ultimately improve their academic well-being.
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