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Reseach Article

Understanding the Postgraduate Education Market for Better Marketing and Decision Making: A Clustering Analysis

by Ali Marstawi, Aida Mustapha
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 91 - Number 12
Year of Publication: 2014
Authors: Ali Marstawi, Aida Mustapha
10.5120/15930-5231

Ali Marstawi, Aida Mustapha . Understanding the Postgraduate Education Market for Better Marketing and Decision Making: A Clustering Analysis. International Journal of Computer Applications. 91, 12 ( April 2014), 1-5. DOI=10.5120/15930-5231

@article{ 10.5120/15930-5231,
author = { Ali Marstawi, Aida Mustapha },
title = { Understanding the Postgraduate Education Market for Better Marketing and Decision Making: A Clustering Analysis },
journal = { International Journal of Computer Applications },
issue_date = { April 2014 },
volume = { 91 },
number = { 12 },
month = { April },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume91/number12/15930-5231/ },
doi = { 10.5120/15930-5231 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:12:31.947075+05:30
%A Ali Marstawi
%A Aida Mustapha
%T Understanding the Postgraduate Education Market for Better Marketing and Decision Making: A Clustering Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 91
%N 12
%P 1-5
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Enhancing the educational corporations is truly challenging mission due to the highly competitive nature of the business. Currently, there is emerging development within organizations to capitalize on their internal resources. This paper is taking data mining approach to strategize marketing for postgraduate studies by means of cluster analysis. The experiments were carried out using Oracle Data Miner tool, results are analyzed and discussed.

References
  1. S. Ayesha, T. Mustafa, A. R. Sattar, and M. I. Khan. Data mining model for higher education system. Europen Journal of Scientific Research, 43(1):24–29, 2010.
  2. J. Han, M. Kamber, and J. Pei. Data Mining Concepts and Techniques. Morgan Kaufman, San Francisco, 3rd edition, 2006.
  3. M. B. Jasser, F. Sidi, A. Mustapha, and A. K. Binhamid. Mining students' characteristics and effects on university preference choice: A case study of applied marketing in higher education. International Journal of Computer Applications, 67(21):1–5, 2013.
  4. V. Kumar and A. Chadha. Mining association rules in student's assessment data. International Journal of Computer Science Issues, 9(5), 2012.
  5. Oracle. Odm: Oracle data miner. http://www. oracle. com/technetwork/database/options/advancedanalytics/ odm/index. html.
  6. C. Romero and S. Ventura. Educational data mining: A survey from 1995 to 2005. Expert Systems with Applications, 33:135– 146, 2007.
  7. C. Romero and S. Ventura. Educational data mining: A review of the state of the art. IEEE Transactions on Systems, Man, and Cybernetics, 40(6), 2010.
  8. F. Siraj and M. A. Abdoulha. Uncovering hidden information within university's student enrollment data using data mining. In Third Asia International Conference on Modeling and Simulation, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Oracle Data Miner Statistical Analysis K-means Clustering