APRIORI ALGORITHM FOR FINDING RELATIONSHIPS BETWEEN STUDENT SELECTION PATHWAYS SCHOOL DEPARTMENTS WITH STUDENT GRADUATION LEVELS

Abstract

The selection process for New Student Admissions (PMB) of State Islamic Universities in Indonesia, especially at UIN Raden Intan Lampung for undergraduate (S1) programs, is pursued through 3 (three) different selection patterns. Selection of SPAN-PTKIN, UM-PTKIN, and UM independent. The three entry paths have their own character, according to their functions and objectives. With these differences, this study identifies the relationship between student entry pathways, majors/types of previous high-level schools with GPA scores, and the length of the study period of students. Data mining in this study is to uses a priori algorithm. The Apriori algorithm is one of the classic data mining algorithms. The a priori algorithm is used to determine the most dominant factor in predicting student graduation rates. A priori algorithms are used so that computers can learn association rules, looking for patterns of relationships between one or more items in a dataset. The data in this study were taken from student data in SIAKAD, namely the student data of Raden Intan Lampung State Islamic University (UIN), Islamic Community Development Department, Class of 2015, the data used included the type of school of origin, entry route, GPA, and length of time. study period. From the results of the research, it is found that the rules or regulations that graduate students with a study period of 4 years / less and a GPA of 3.51 - 4.00 are students who enter through the Academic Interest (PMA) search path and from their school of high school (SMAN) with Value Support. 14,286 and 60% confidence value. These results can be used by universities in encouraging students from other entry paths and from other schools to graduate on time, such as students who entered through the PMA route and from high school from SMAN with certain efforts.