Application of Data Mining for Student Satisfaction Analysis of Offline Learning Performance in the Department of Public Health With the C4.5 Algorithm Method

Abstract

Students become one of the most vital assets for a higher education institution, and in this case, students as consumers who enjoy educational services in higher education need to get consideration whether they are satisfied or dissatisfied with the services provided. One of the ways to increase learning motivation is to provide good educational services quality to students. Because if students are satisfied with the campus services they receive, they will be more active in attending lectures, as well as in participating in other student activities. Previously at the UMKT, there had never been a measurement of student satisfaction at the study program level. To determine the level of student satisfaction needs to do analyzed. Analysis can be done with classification techniques using the decision tree algorithm/C4.5. Because the C4.5 Algorithm is widely used, it has major advantages over other algorithms. The advantages of the C4.5 Algorithm are that it can produce a decision tree that is easy to interpret, has an acceptable level of accuracy, and is efficient in handling discrete and numeric type attributes. In this research, a decision tree was formed and gave information that the main variable that affects student satisfaction in the Department of Public Health is "Administration services in the Department are easy and fast". And the result of calculating the accuracy value is 83%.