CFP last date
22 April 2024
Reseach Article

Implementation of Apriori Algorithm to Analyze Organization Data: Building Decision Support System

by Abdullah Saad Al-malaise
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 66 - Number 9
Year of Publication: 2013
Authors: Abdullah Saad Al-malaise
10.5120/11113-6070

Abdullah Saad Al-malaise . Implementation of Apriori Algorithm to Analyze Organization Data: Building Decision Support System. International Journal of Computer Applications. 66, 9 ( March 2013), 23-27. DOI=10.5120/11113-6070

@article{ 10.5120/11113-6070,
author = { Abdullah Saad Al-malaise },
title = { Implementation of Apriori Algorithm to Analyze Organization Data: Building Decision Support System },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 66 },
number = { 9 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume66/number9/11113-6070/ },
doi = { 10.5120/11113-6070 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:22:28.244741+05:30
%A Abdullah Saad Al-malaise
%T Implementation of Apriori Algorithm to Analyze Organization Data: Building Decision Support System
%J International Journal of Computer Applications
%@ 0975-8887
%V 66
%N 9
%P 23-27
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Building decision support system is major concern for almost every organization to get decisions on daily processes. In current market situation automated decision support systems can produce more alternatives (multi criterion) for decision makers. In this paper we propose automated decision support system with integration of data mining techniques. Building system with amalgamation of both techniques showing feasible approach that can produce appropriate results and fast processing. In presented model the data mining (DM) abstract will support to generate new rules and patterns on customers/employees queries and data. Whereas decision support system (DSS) abstract can ask help from DM databases online or offline to provide multi criterion alternatives. The main purpose of this model is to help decision makers by using multi criteria decision making strategy with DM techniques as those consider powerful tool for decision making processes. In the end we have provided practical implementation using some real world data, to show step by step meaningful purpose of the proposed model.

References
  1. Abdullah Saad Almalaise Alghamdi, "Efficient Implementation of FP Growth Algorithm Data Mining on Medical Data", International Journal of Computer Science and Network Security (IJCSNS)-2011.
  2. Efraim Turban, Ramesh Sharda, Dursun Delen, Decision Support and Business Intelligence, 9th Edition, published by Pearson Education, Prentice Hall-2011.
  3. Apriori Algorithm, http://en. wikipedia. Org /wiki/Apriori algorithm #Algorithm, Last accessed Date: 1st January, 2013.
  4. Agrawal R, Imielinski T, Swami AN. "Mining Association Rules between Sets of Items in Large Databases. " SIGMOD. June 1993, 22(2):207-16.
  5. Osmar R. Zaïane, "Chapter I: Introduction to Data Mining", CMPUT690 Principles of Knowledge Discovery in Databases, 1999.
  6. http://office. microsoft. com/en-001/excel-help/ introduction-to-what-if-analysis-HA010243164. aspx, last accessed date, 15th January, 2013.
  7. Abdullah Al- Mudimigh, Farrukh Saleem, Zahid Ullah, The Effects Of Data Mining In ERP-CRM Model – A Case Study Of MADAR, WSEAS Transaction, 2009
  8. Dr. Abdullah Al- Mudimigh, Farrukh Saleem, Zahid Ullah, The Role Of Data Mining In ERP-CRM Model", International Conference on Applied Computer & Applied Computational Science (ACACOS '09), Hangzhou, China, 2009.
  9. Data Mining for Customer Queries in ERP Model- A Case Study of MADAR", IEEE / ICICT-2009, Third International Conference on Information & Communication Technologies, Karachi, Pakistan, 2009.
  10. Dr. Abdullah Al- Mudimigh, Farrukh Saleem, Zahid Ullah, Efficient Implementation of Data Mining: Improve Customer's Behavior", The 7th IEEE/ACS, International Conference on Computer Systems and Applications, Rabat, Morocco, to be held on May, 10-13, 2009.
  11. Pang-Ning Tan, Michael Steinbach & Vipin Kumar, "Introduction to Data Mining", Addison Wesley, 2005, ISBN 0321321367
  12. Jiawei Han, Micheline Kamber, Jian Pei, "Data Mining: Concepts and Techniques", 2nd edition, 2005, Morgan Kaufmann, ISBN 1558609016
  13. Farrukh Saleem, Areej Malibari, Data Mining Course in Information System Department–Case Study of King Abdulaziz University, IEEE, ICEED- 3rd International Congress on Engineering Education, 7th – 8th December, 2011.
  14. Farrukh Saleem, Abdullah Al-Malaise, Implementation of Data Mining Approach for Building Automated Decision Support Systems, International Conference on Information Society (i-Society 2012), IEEE, June 25-28, 2012, London, UK.
  15. Fernando Toro and Roberto Mayerle, A Decision Support System for Enhancing Model Development and Application, Esri International Conference-2001.
  16. Hai Wang, Shouhong Wang, Medical Knowledge Acquisition through Data Mining, Proceedings of 2008 IEEE International Symposium on IT in Medicine and Education.
  17. T. L. Saaty. Relative Measurement and Its Generalization in Decision Making. Why Pairwise Comparisons are Central in Mathematics for the Measurement of Intangible Factors. The Analytic Hierarchy/Network Process. Rev. R. Acad. Cien. Serie A. Mat. VOL. 102 (2), 2008, pp. 251–318
Index Terms

Computer Science
Information Sciences

Keywords

Decision Models Association Mining Knowledge Management