Student Performance Analysis System (SPAS)

Chew, Li Sa and Dayang Hanani, Abang Ibrahim and Emmy Dahliana, Hossain and Mohammad, Hossin (2015) Student Performance Analysis System (SPAS). The 5th International Conference on Information and Communication Technology for The Muslim World (ICT4M), 2014. ISSN ISBN: 978-1-4799-6242-6

[img]
Preview
PDF
Student Performance Analysis System (SPAS)(abstract).pdf

Download (142kB) | Preview

Abstract

Almost every university have their own management system to manage the students' records. Currently, even though there is a student management system that manages the students' records in Universiti Malaysia Sarawak (UNIMAS), no permission is provided for lecturers to access the system. This is because the access permission is only to top management such as Deans and Deputy Deans of Undergraduate and Student Development due to its privacy setting. Thus, this project proposes a system named Student performance analysis system (SPAS) to keep track of students' result in the Faculty of Computer Science and Information Technology (FCSIT). The proposed system offer a predictive system that is able to predict the students' performance in course “TMC1013 System Analysis and Design”, which in turns assists the lecturers from Information System department to identify students that are predicted to have bad performance in course “TMC1013 System Analysis and Design”. The proposed system offers student performance prediction through the rules generated via data mining technique. The data mining technique used in this project is classification, which classifies the students based on students' grade.

Item Type: Article
Uncontrolled Keywords: Student performance; student analysis; data mining; student performance analysis; classification; prediction; system, research, Universiti Malaysia Sarawak, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education
Subjects: L Education > L Education (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Karen Kornalius
Date Deposited: 12 Jun 2017 04:10
Last Modified: 12 Jun 2017 04:10
URI: http://ir.unimas.my/id/eprint/16598

Actions (For repository members only: login required)

View Item View Item