<![CDATA[The implementation of the Reduce, Reuse, and Recycle (3R) program in educational institutions plays a strategic role in fostering environmental awareness from an early age; however, its evaluation has often relied on descriptive approaches rather than objective data-driven analysis. This study aims to analyze the level of success of the 3R program implementation in schools and to identify the key factors influencing its success using a data mining approach with the C4.5 algorithm. A quantitative descriptive-analytic method was employed, utilizing primary data collected through observation and documentation of 3R program activities in schools. The data analysis followed the knowledge discovery in databases (KDD) process, including data selection, preprocessing, transformation, modeling, and evaluation. The results indicate that the C4.5 algorithm achieved a classification accuracy of 98.94%, demonstrating excellent model performance. The generated decision tree reveals that student participation is the most influential factor in determining the success of the 3R program, followed by parental involvement and teacher support. These findings suggest that the success of the 3R program is not solely determined by school policies, but largely depends on the active participation of key educational stakeholders. This study provides practical implications for schools and policymakers by offering a data-driven evaluation model that supports more objective decision-making and promotes the integration of environmental programs into the learning process within educational institutions.]]>
