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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2012 Vol.4(4): 533-536 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2012.V4.526

Six Sigma Methodology with Recency, Frequency and Monetary Analysis Using Data Mining

Andrej Trnka

Abstract—Data Mining methods provide a lot of opportunities in the market sector. This paper deals with Data Mining algorithms and methods (especially RFM analysis) and their use in Six Sigma methodology, especially in DMAIC phases. DMAIC stands for Define, Measure, Analyze, Improve and Control. Our research is focused on improvement of Six Sigma phases (DMAIC phases). With implementation of RFM analysis (as a part of Data Mining) to Six Sigma (to one of its phase), we can improve the results and change the Sigma performance level of the process. We used C5.0, QUES, CHAID and Neural Network algorithms. The results are in proposal of selected Data Mining methods into DMAIC phases.

Index Terms—Data mining; DMAIC, RFM, six sigma.

Andrej Trnka is with the University of SS Cyril and Methodius in Trnava, Faculty of Mass Media Communication, Nam. J. Herdu 2, 917 01 Trnava, Slovak Republic (e-mail: andrej.trnka@ucm.sk).


Cite: Andrej Trnka, "Six Sigma Methodology with Recency, Frequency and Monetary Analysis Using Data Mining," International Journal of Computer Theory and Engineering vol. 4, no. 4, pp. 533-536, 2012.

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