USING THE C4.5 ALGORITHM TO BUILD A DECISION TREE FOR THE CAREER CHOICE PROBLEM OF HIGH SCHOOL STUDENTS IN THAI NGUYEN PROVINCE

Abstract

In this study, a decision tree was built and the career selection results of grade-12 students in Thai Nguyen province were predicted by algorithm C4.5. Research results have shown that this decision tree has high accuracy and is built based on data collection and preprocessing. However, it is found that the study can only be applied to Thai Nguyen province and needs to be optimized to give more accurate prediction results. Data was collected through a questionnaire of 900 grade-12 students at Ngo Quyen, Tran Quoc Tuan, and Dong Hy high schools in Thai Nguyen province. The author used primary factors to assess, including social needs, learning outcomes, family economic conditions, place of residence and gender. Research results showed that the social needs and learning ability were factors that have a great impact on students’ intention to choose a career. At the same time, the classification based on algorithm C4.5 was confirmed to bring higher classification accuracy than the technique based on the Bayes algorithm. This research can contribute to support the university admissions process as well as to help guide the careers of high school students, mainly in grade 12.