FACTORS AFFECTING INTERNAL QUALITY ASSESSMENT SCORES FOR FACULTIES OF PHRANAKHON SI AYUTTHAYA RAJABHAT UNIVERSITY THROUGH AN APPLICATION OF THE DATA MINING TECHNIQUES

Abstract

The research purposes were study the factors affecting the quality of education within the faculty level in Phranakhon Si Ayutthaya Rajabhat University and compare the model for assessing quality of education at the faculty level by using data mining model and applied during multiple regression analysis, decision tree ,Artificial Neural Network, Naive Bayes and K-Nearest Neighbors. The data use from the evaluation of quality education in the faculty level of Phranakhon Si Ayutthaya Rajabhat University during for the academic year 2014-2016 , 3 years ,4 faculties total 12 records. From using the 5 criteria rating indicators, results of multiple regression analysis found that element no. 4, preserving arts and culture, was the highest valuable and secondary was the research which showed that the most important factor in evaluating the quality of internal education. When comparing the model of quality assessment in the faculty was the best and found that Artificial Neural Network average error value (MAE) was 0.0249 K-Nearest Neighbors average error value (MAE) was 0.0714, Naive Bayes average error value (MAE) was 0.1176 and decision tree average error value (MAE) was 0.1500. Therefore the model of Artificial Neural Network suited for the quality of education in the faculty. The research results found that in Phranakhon Si Ayutthaya Rajabhat University should encouraging lectures responsible the promoting the preservation of arts and culture also more researching which will increase , internal quality education assessment in faculty.