Enhancing The Quality of College Decisions Through Decision Tree and Random Forest Models - Sitti Rahmah Jabir; Huzain Azis; St. Hajrah Mansyur (Program Studi Teknik Komputer, 2024)
One of the key indicators of the growth of a college is the number of students that are enrolled in the institution on an annual basis. Student enrollment is a crucial element in the growth of a college, particularly in the case of private institutions. When examining students' aspirations for higher education, several studies use data mining techniques to forecast the interests of students who will pursue college. Researchers adopt various ways to extract valuable information from data. Prior research has shown that the decision tree technique outperforms alternative methods. The random forest, in addition to the decision tree, is often used for predicting data mining tasks. Given the above background information, the author will conduct a study titled