Strengthening campus finance by analyzing attribute attributes for student registration classifications

Abstract

Students are the most valuable assets in a private college. Assets like this that really need to be maintained and maintained, because most of the income from the private campus is derived from the tuition fees of students. The large number of students who resigned and did not conduct registration would have an impact on the financial institutions. STMIK Widya Pratama is the only computer science campus in Pekalongan City. Data from the last 5 years obtained from the new student admissions committee at STMIK Widya Pratama Pekalongan shows that out of 2670 prospective students who enroll, there are at least 514 prospective students who do not register. This means that around 20% of students do not register. Several analyzes related to the classification for student registration were conducted. In this case the best method that can be used is C45. In the process of calculating the C45 algorithm, information gain method is used to determine the importance of data attributes. The calculation results show that the attribute with the highest level of importance is the city_district attribute from the prospective student's residence, followed by the attributes of education, parental education, and tuition. These results can later be used and developed to create a system to support campus policy.