Prediction model on graduate employment based on Bayesian Belief Network Classification Method for decision support system

Abstract

Currently, there is a huge amount of data stored in educational database, this this database contains hidden information for analyzing available data and extracting information and knowledge to support decision-making. Organization has a desire to extract hidden but useful knowledge in predicting undergraduate employment. The most useful data mining technique in educational database is classification such as Bayesian method used in this study. Further, it uses a classification task in WEKA where classification models were generated. To validate the generated model, the experiments were conducted using real data collected from the graduate profile of the West Visayas State University. The result was a good model intended to be used in predicting graduate employment data.