Predicting scholarship grants using data mining techniques

Abstract

Almost all major colleges and state universities assess students' comprehensive quality and set different rewards and regulations for the various level in order to stimulate students' interest to study and participate in extracurricular activities. The main reward system that is used is the providing of financial incentives such as scholarship grants. In this paper, several data mining techniques such as clustering and forecasting was integrated to discover and assess future outcomes and matters concerning The Student Financial Assistance Unit (SFAU) of Surigao State College of Technology (SSCT) holds all the records of scholarship grants and its grantees from June 2014. The study visualizes the increase of the grantees in every scholarship grants in the next five years to prepare the budget that needs to be allocated by the sponsoring agents. ARIMA(1,0,0) model for time series analysis was used in the study and found out to be very effective as it produced results as shown in Fig. 11-23.