doi: 10.7763/IJCTE.2012.V4.526
Six Sigma Methodology with Recency, Frequency and Monetary Analysis Using Data Mining
Andrej Trnka
- University of SS Cyril and Methodius in Trnava, Faculty of Mass Media Communication, Nam. J. Herdu 2, 917 01 Trnava, Slovak Republic.
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.
Keywords
- Data mining; DMAIC
- RFM
- six sigma
How to 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. https://doi.org/10.7763/IJCTE.2012.V4.526
Copyright & License
Copyright © 2012 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).