Klasifikasi Kelayakan Penerima Beasiswa Menggunakan Algoritma Decision Tree

The scholarship selection process is a crucial activity in higher education, ensuring that educational assistance is provided to students who truly need it. However, due to the large number of applicants and various criteria required, such as GPA, parental income, number of dependents, organizational membership, and other factors, the selection process becomes more complex. Therefore, a method is needed to facilitate a more objective and efficient decision-making process. This study aims to categorize those eligible for scholarships using the Decision Tree method. The method used is data mining with classification techniques. The dataset used includes several attributes such as gender, year of graduation, cumulative grade point average, number of credits, distance from residence to campus, parents' occupation, parents' income, membership in an organization, involvement in a small or medium-sized business, number of dependents in the family, and scholarship recipient status. The data processing process was carried out using the RapidMiner application through several stages: data selection, data preparation, data transformation, Decision Tree model creation, and model quality checking. The results show that the dependent factor has the greatest influence in determining whether someone is eligible or not.