The Development of Model for Online Autonomous Decision Support Systems for Managing the Study Plan of Students in Higher Education
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Abstract
- This research aims to create a model for determining factor that influences student on choosing majors in higher education. It also develops a model for online autonomous decision support system for guiding the study plan for student in higher education. The research has created a probabilistic model by employing WEKA (Waikato Environment for Knowledge Analysis) software based on data mining technique. The result from the model was validated according to K-fold cross validation method. The best result from Bayesian belief network technique was used as an input in creating the final model. The model accuracy was then compared with the deteriorate manner multiple regression analysis. In doing this, the researcher has used educational data from sample group consisting of undergraduates from 9 public and private universities. Result from the research has shown that probability model using data mining technique in accordance with Bayesian belief network can indicate the factors that significantly influence student on choosing major in higher education and give accuracy in prediction as high as 91.35 in percentage. According to the model, the important factors that affect the student decision on choosing major in higher education are the grade point of average in Mathematics prior to and during the study, grade point of average in Programming subject, knowledge to develop software and computer system, knowledge in subject 1 and subject 2, and student aptitude. In addition, the subject factor derived from the model is also consistent with the result from the Multiple Regression Analysis. It is therefore believed that the factors resulted from the model of decision support system based on Bayesian belief network theory as mentioned in this research is reliable in an acceptable level.
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