Mining Least Association Rules of Degree Level Programs Selected by Students

One of the most popular and important studies in data mining is association rules mining. Generally, association rules can be divided into two categories called frequent and least. However, finding the least association rules is more complex and time consuming as compared to the frequent one. These...

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Main Authors:	Zailani, Abdullah, Herawan, Tutut, Noraziah, Ahmad, Mustafa, Mat Deris
Format:	Article
Language:	English
Published:	SERSC 2014
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/6614/ http://umpir.ump.edu.my/id/eprint/6614/ http://umpir.ump.edu.my/id/eprint/6614/ http://umpir.ump.edu.my/id/eprint/6614/1/23.pdf

id	ump-6614
recordtype	eprints
spelling	ump-66142018-02-02T07:29:26Z http://umpir.ump.edu.my/id/eprint/6614/ Mining Least Association Rules of Degree Level Programs Selected by Students Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris QA75 Electronic computers. Computer science One of the most popular and important studies in data mining is association rules mining. Generally, association rules can be divided into two categories called frequent and least. However, finding the least association rules is more complex and time consuming as compared to the frequent one. These rules are very useful in certain application domain such as determining the exceptional association between university’s programs being selected by students. Therefore in this paper, we apply our novel measure called Definite Factors (DF) to determine the significant least association rules from undergraduate’s program selection database. The dataset of computer science student for July 2008/2009 intake from Universiti Malaysia Terengganu was employed in the experiment. The result shows that our measurement can mine these rules and it is at par with the existing benchmarked Relative Support Apriori (RSA) measurement. SERSC 2014 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/6614/1/23.pdf Zailani, Abdullah and Herawan, Tutut and Noraziah, Ahmad and Mustafa, Mat Deris (2014) Mining Least Association Rules of Degree Level Programs Selected by Students. International Journal of Multimedia and Ubiquitous Engineering (IJMUE), 9 (1). pp. 241-254. ISSN 1975-0080 http://www.sersc.org/journals/IJMUE/vol9_no1_2014/23.pdf DOI: 10.14257/ijmue.2014.9.1.23
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris Mining Least Association Rules of Degree Level Programs Selected by Students
description	One of the most popular and important studies in data mining is association rules mining. Generally, association rules can be divided into two categories called frequent and least. However, finding the least association rules is more complex and time consuming as compared to the frequent one. These rules are very useful in certain application domain such as determining the exceptional association between university’s programs being selected by students. Therefore in this paper, we apply our novel measure called Definite Factors (DF) to determine the significant least association rules from undergraduate’s program selection database. The dataset of computer science student for July 2008/2009 intake from Universiti Malaysia Terengganu was employed in the experiment. The result shows that our measurement can mine these rules and it is at par with the existing benchmarked Relative Support Apriori (RSA) measurement.
format	Article
author	Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris
author_facet	Zailani, Abdullah Herawan, Tutut Noraziah, Ahmad Mustafa, Mat Deris
author_sort	Zailani, Abdullah
title	Mining Least Association Rules of Degree Level Programs Selected by Students
title_short	Mining Least Association Rules of Degree Level Programs Selected by Students
title_full	Mining Least Association Rules of Degree Level Programs Selected by Students
title_fullStr	Mining Least Association Rules of Degree Level Programs Selected by Students
title_full_unstemmed	Mining Least Association Rules of Degree Level Programs Selected by Students
title_sort	mining least association rules of degree level programs selected by students
publisher	SERSC
publishDate	2014
url	http://umpir.ump.edu.my/id/eprint/6614/ http://umpir.ump.edu.my/id/eprint/6614/ http://umpir.ump.edu.my/id/eprint/6614/ http://umpir.ump.edu.my/id/eprint/6614/1/23.pdf
first_indexed	2023-09-18T22:02:33Z
last_indexed	2023-09-18T22:02:33Z
_version_	1777414494642765824

Mining Least Association Rules of Degree Level Programs Selected by Students

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