Classifying Student Academic Performance: A Hybrid Approach

Nowadays, organizations are overwhelmed with a large amount of electronic data that require proper management to discover previously hidden knowledge. Having a set of non-transformed data may be a huge waste as specific processes onto the data would result in the discovery of valuable knowledge. Thi...

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Main Authors: Ahmad I. Z. Abidin , A, Yong, S.P., Foong, Oi Mean, Ahmad , Jale, Ili A. Setu, I.
Format: Conference or Workshop Item
Language:English
Published: 2007
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/1182/
http://scholars.utp.edu.my/id/eprint/1182/1/IMECS_19March08.pdf
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author Ahmad I. Z. Abidin , A
Yong, S.P.
Foong, Oi Mean
Ahmad , Jale
Ili A. Setu, I.
author_facet Ahmad I. Z. Abidin , A
Yong, S.P.
Foong, Oi Mean
Ahmad , Jale
Ili A. Setu, I.
author_sort Ahmad I. Z. Abidin , A
building UTP Institutional Repository
collection Online Access
description Nowadays, organizations are overwhelmed with a large amount of electronic data that require proper management to discover previously hidden knowledge. Having a set of non-transformed data may be a huge waste as specific processes onto the data would result in the discovery of valuable knowledge. This paper discusses the development of a predictive model to classify undergraduate students’ class of graduation: first class, second upper division, second class lower division, or third class. Techniques used to support the classification are implemented in using back propagation feed forward neural network with Bayes probability.
first_indexed 2025-11-13T07:24:47Z
format Conference or Workshop Item
id oai:scholars.utp.edu.my:1182
institution Universiti Teknologi Petronas
institution_category Local University
language English
last_indexed 2025-11-13T07:24:47Z
publishDate 2007
recordtype eprints
repository_type Digital Repository
spelling oai:scholars.utp.edu.my:11822017-01-19T08:27:00Z http://scholars.utp.edu.my/id/eprint/1182/ Classifying Student Academic Performance: A Hybrid Approach Ahmad I. Z. Abidin , A Yong, S.P. Foong, Oi Mean Ahmad , Jale Ili A. Setu, I. QA75 Electronic computers. Computer science Nowadays, organizations are overwhelmed with a large amount of electronic data that require proper management to discover previously hidden knowledge. Having a set of non-transformed data may be a huge waste as specific processes onto the data would result in the discovery of valuable knowledge. This paper discusses the development of a predictive model to classify undergraduate students’ class of graduation: first class, second upper division, second class lower division, or third class. Techniques used to support the classification are implemented in using back propagation feed forward neural network with Bayes probability. 2007 Conference or Workshop Item PeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/1182/1/IMECS_19March08.pdf Ahmad I. Z. Abidin , A and Yong, S.P. and Foong, Oi Mean and Ahmad , Jale and Ili A. Setu, I. (2007) Classifying Student Academic Performance: A Hybrid Approach. In: International Multi-Conference of Engineers and Computer Scientists (IMECS) 2007, 21 - 23 March 2007, Hong Kong.
spellingShingle QA75 Electronic computers. Computer science
Ahmad I. Z. Abidin , A
Yong, S.P.
Foong, Oi Mean
Ahmad , Jale
Ili A. Setu, I.
Classifying Student Academic Performance: A Hybrid Approach
title Classifying Student Academic Performance: A Hybrid Approach
title_full Classifying Student Academic Performance: A Hybrid Approach
title_fullStr Classifying Student Academic Performance: A Hybrid Approach
title_full_unstemmed Classifying Student Academic Performance: A Hybrid Approach
title_short Classifying Student Academic Performance: A Hybrid Approach
title_sort classifying student academic performance: a hybrid approach
topic QA75 Electronic computers. Computer science
url http://scholars.utp.edu.my/id/eprint/1182/
http://scholars.utp.edu.my/id/eprint/1182/1/IMECS_19March08.pdf