Abstract—Data mining is the process of discovering
knowledge which in turn can be used to predict future trends.
On the other hand, decision support system is an information
system that enables one to analyze data and compile
information that will aid in decision making process. This paper
presents the integration of data mining and decision support
system in an educational context. thus, a predictive decision
support system for licensure examination performance
(PDSS-LEP) is designed that highlights the repeated generation
of multiple regression model and the integration of another
classification model which was derived using PART
classification technique. The PDSS-LEP was found beneficial as
it provides a good platform for generation of MR model that
can be adapted by other institutions because of its model
selection procedures and user-oriented interface. It is however
suggested that data integration should be enhanced by
considering multiple sources of data.
Index Terms—Data mining and decision support system
integration, LET performance, multiple regression, predictive
decision support system.
I. M. Tarun is with the Isabela State University, Isabela, Philippines
(e-mail: ivy_tarun@yahoo.com).
B. D. Gerardo is with West Visayas State University, Iloilo, Philippines.
(e-mail: bgerardo@wvsu.edu.ph).
B. D. Tanguilig III is with the College of Information Technology
Education, Technological Institute of the Philippines, Quezon City,
Philippines (e-mail: bttanguilig_3@yahoo.com).
[PDF]
Cite: Ivy M. Tarun, Bobby D. Gerardo, and Bartolome T. Tanguilig III, "Predictive Decision Support System for Licensure
Examination Performance through Integration of Multiple
Regression and PART Classification Models of Data Mining," International Journal of Modeling and Optimization vol. 4, no. 5, pp. 390-394, 2014.
