Analysis of Study Program Selection Patterns Using FP-Growth and ECLAT Methods

Nurbojatmiko, Eri Rustamaji, Asep Fajar Firmansyah

Abstract: A set of data that correlates form patterns. In determining the patterns of data sets using association rules. The University has a variety of faculties that have several study programs. Many factors that influence prospective students determining the choice of their study program. Researchers consider it important to look for patterns of prospective students in determining their study program choices. With these patterns can help prospective students determining their choices. Forming these patterns uses the association rules with the FP-Growth and ECLAT methods. Researchers conducted a survey to students from various universities on the island of Java, Indonesia. Of the 35 transaction data obtained, the support minimum value is 20% and the confidence value is 45%. There are some association rules obtained, namely 12 rules using FP-Growth algorithm and 9 rules using ECLAT algorithm. Of these rules, interest factors, accreditation, and job prospects are the main factors influencing the choice of study programs.