<![CDATA[This study aims to analyze the relationship between students’ daily habits and their academic performance using the C4.5 algorithm. The daily habit variables examined include study duration and intensity, sleep quality and patterns, frequency and type of gadget use, attendance consistency, and students’ engagement in learning activities both inside and outside the classroom. The data were collected through questionnaires and combined with students’ academic grades as indicators of performance. The C4.5 algorithm was employed to construct a decision tree model capable of identifying the daily habit attributes that have the most significant influence on academic achievement. The findings reveal that study intensity, sleep quality, and attendance consistency serve as dominant factors in predicting students’ performance levels. Furthermore, the resulting decision tree model demonstrates a relatively high accuracy level, making it a useful tool for evaluation, student development planning, and decision-making processes by educators. These results confirm that the application of the C4.5 algorithm is effective in uncovering the relationship patterns between daily habits and academic achievement and has the potential to serve as a reference for efforts to improve students’ learning quality.]]>
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