WEB BASED ADMISSION RECOMMENDER SYSTEM INTO TERTIARY INSTITUTIONS

Abstract

Education plays a vital role in the lives of every individual; it encourages growth and promotes values and culture. University Education is an important part that prepare most people for working life. So, choosing the right course in these formative years is a very important decision as life depends on it. Pre-tertiary students tend to be confused at this stage because there are lots of pressures from the society. This Research therefore developed a Web Based Admission Recommender System that assists Pre-tertiary students to independently choose a course of study based on their abilities. The system considered three major parameters which is favourite core subjects combination, Intelligence Quotient and Career Interest. It was implemented with principle of Catboost Classification using Gradient Boosting Algorithm, the user interface was designed using Bootstrap 3, the programming language is Python and Flask as the framework. The system was implemented and evaluated using 346 pretertiary students. The feedback shows that the system is 86.71% accurate, 74.4% precise, 80% satisfactory, and 83% valid.