1. Data mining decision tree algorithm C4.5 classification of student personality characteristics.
- Author
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Selvida, Desilia, Pulungan, Annisa Fadhillah, and Elveny, Marischa
- Subjects
- *
CLASSIFICATION algorithms , *ABILITY grouping (Education) , *DATA mining , *DECISION trees , *ERROR rates , *ALGORITHMS - Abstract
The C4.5 algorithm still has weaknesses in predicting or classifying data if the amount is large. It is necessary to improve the performance of the C4.5 algorithm with the selected split attribute using application of the average gain value to perform the classification. The C4.5 algorithm is one of the Decision Tree methods in the classification process using entropy. The result of the classification obtained from the analysis can be a classification of 8 student data from 100 student data that is tested to produce information on Sanguine, Choleric, Melancholy, and Phlegmatic. From the result of the Decision Tree classification algorithm C4.5 has an accuracy rate of 86.36% with an application error rate or error of 13.64%. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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