The Design of Polynomial Curve Fitting Model A Prediction of Freshmen Enrolment and a Recommender System

Nowadays, as far as mathematical knowledge is concerned, primary forecasting techniques are needed to aid institutions or companies to generate a strategy for the future. Forecasting is one of the important tools for developing strategic choices that is thought as a vital part for valuable organization. The main aim of this study is twofold: to design a Polynomial Curve Fitting-Model based on freshmen enrolment report and to develop a recommender system that will aid the Higher Education Institution management for decision making. The researcher used descriptive method of research using historical and documentary analysis, backed by respondents composed of school admission and registrar staff and some college officials and administrators. The researcher used participant observation and informal interview. The study shows that Polynomial Curve Fitting Model can also be used to forecast enrolment data and the factors that affect student enrolment but comparing it with the other time series forecasting techniques, its Mean Absolute Percentage Error (MAPE) is high. The results of this study will be used by the decision maker to achieve some sets of institutional goals and can be a basis for long-range planning. Therefore, it is important to note that enrolment forecasting is an iterative and collaborative process, with models being annually reviewed based on feedback from various constituents within the community.

Keywords – Data Mining, Polynomial Curve Fitting, Prediction, Recommender System