Attribute Analysis of Program Selection Under TCAS System by Data Mining Techniques
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Abstract
The objectives of this research were to: 1) analyze the characteristics of applicants selecting programs under the TCAS system using Data Mining techniques, and 2)develop a model based on the analysis results to support public relations, information dissemination, and admissions planning for the MahaSarakham University TCAS system. The target group consisted of applicants for bachelor's degree programs under the TCAS system during the academic years 2018–2021. The research utilized a dataset comprising 58,110 applicant records. The data analysis employed statistical methods, specifically Association Rule Mining using the Apriori Algorithm.
The results showed as follows: 1) The analysis of applicant characteristics in selecting programs under the TCAS system revealed that key factors influencing program selection included gender, province, General Aptitude Test (GAT) scores, and Professional and Academic Aptitude Test (PAT) scores. The confidence level of the association rules was set at 80 percent (Confidence = 0.8) to ensure high reliability, and the model developed from the analysis results was designed to support public relations, information dissemination, and admissions planning for the TCAS system at MahaSarakham University. A total of 36 association rules were generated. These association rules can be effectively used as decision-making tools to guide public relations strategies and enhance the program selection process for prospective applicants at MahaSarakham University.
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References
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