การเปรียบเทียบประสิทธิภาพโมเดลการตัดสินใจเลือกกลุ่มวิชาของนักศึกษา สาขาวิชาเทคโนโลยีสารสนเทศ คณะวิทยาศาสตร์ มหาวิทยาลัยราชภัฏบุรีรัมย์

Abstract

The objective of this research was to compare the efficiency of decision making models on major selection of Information Technology students of Faculty of Science in Buriram Rajabhat University by using 3 data mining techniques: Decision Tree , Naïve Bayes, and Neural Network. The data derived from the data record with 16 characteristics of 407 students from 2012-2017 were used in developing the model prototype by using RapidMiner Studio 9. Some data were also used in the tryout using 10-Fold Cross Validation to find the efficiency by comparing from Accuracy, Recall, Precision and F-measure. The findings from the comparison indicated that Decision Tree offered the most accuracy value. When classified by each major, it was found that Information Technology major had the accuracy value of 94.17% while Computer Technology major had 88.72% and Computer Management for Education major had 92.87%. It can be concluded that Decision Tree model had the most efficiency.