Optimizing the Accuracy of the C4.5 Algorithm Using the Adaptive Boosting Method to Predict Students Receiving Education Funds
DOI:
https://doi.org/10.70609/gtech.v8i4.5612Keywords:
Adaboost, Algorithm C4.5, Machine LearningAbstract
The importance of increasing accuracy for educational institutions in predicting the provision of educational financial assistance. To make decisions about who deserves education funding. Data processing on aid recipients can be processed into information. This study aims to improve the accuracy of the C4.5 algorithm by using adaboost to determine whether students deserve to receive educational assistance funds or not by comparing the results before and after implementing adaboost. Predicting students' eligibility for obtaining educational assistance funds using decision trees. The dataset was collected from 414 students of SMK Muhammadiyah 1 Ngoro, used for this research. The research results show an increase in accuracy of 2.69% with the application of the C4.5 algorithm which has an accuracy of 77.31%, while the accuracy with the application of Adaboost reaches 80%.
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