<![CDATA[Online learning is an educational process conducted through the internet. This is a new concept for students and requires adjustment. This method can impact student understanding, as each individual has a unique level of comprehension. This application was developed using the CRISP-DM methodology, which is an industry standard for data mining. Flowcharts are used to illustrate the process of creating applications and implementing algorithms, while DFDs are used to depict data flow. The data for this research was obtained from questionnaires distributed to 198 students. The research results show that the application implementing the C5.0 algorithm to determine the level of student understanding of online learning materials during the covid-19 pandemic has been successfully implemented and functions well, with a student understanding level of 60%. However, this figure is still considered low. Based on the decision tree results generated by the C5.0 algorithm, the communication attribute is the most influential factor in online learning. Therefore, to improve student understanding, an increase in multi-directional based learning is needed.]]>
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