Association Rule Discovery for Selecting Programs in TCAS

Abstract

Mahasarakham University (MSU) has pursued the undergraduate application recruitment under the policy set forth by the Ministry of Higher Education, Science, Research and Innovation (MHESI) which prescribes that the universities are required to partake in the Thai University Central Admission System (TCAS). From the year 2018 to the present that the MSU has joined TCAS, the MUS found several problems such as a declining number of applicants, the unforeseen tendency of the number of prospective applicants, unspecified prospective applicants, and unknown applicants characteristics in selecting programs in a sequence. In this study, the Mining Association Technique was proposed with the Apriori Algorithm. The high reliability of the mining association was 80.00 percent The results showed that the factors affecting the undergraduate program selection mostly included General Aptitude (GAT) scores, Professional and Academic Aptitude (PAT) scores, school size, school location, and applicant’s gender respectively. The results obtained are expected to be used to design data relationships for selecting programs for the applicants and be further used for planning the undergraduate applicant selection in the MSU’s TCAS system.