A Computer’s Course Recommender System Based On Learner Characteristic Analysis By Ontology

Abstract

This study describes the system for suggestion further education at the bachelor's degree by using
characteristics learner analysis methods that match the nature of courses. Moreover, this time, we
chose an introduction to computer courses were Computer Science (CS), Information Technology
(IT), and Web Programming and Security (WEB). The main objective is to develop a computer course
recommender system to match the learner's characteristics (called CCL-guidance system). It is a
website, so separating into two parts are 1) Database Website used to input learner profile data,
created by PHP and MySQL, and 2) Semantic Web used to provide guidance results, courses
matching the learner's characteristic, constructed from OAM tools. The system made up from
conceptual ontology all three modules as follows: 1) Learner Profile Module, it designed to analyze
learner characteristics, 2) Computer Course Module, it designed to analyze the identity of all
computer courses, and 3) Result_learner_Recommend Module, it used to guide course to the learner.
We found that the experiment results are Learner Characteristic Group (LCG) to most match the
identity of 3 courses, including LCG2: CS, LCG1: IT, and LCG5: Web.