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Data Mining Approach to Decision Support in Social Welfare

Author

Listed:
  • Ricardo Anderson

    (Department of Computing, The University of the West Indies, Mona-Western Jamaica Campus, Jamaica)

  • Gunjan Mansingh

    (Department of Computing, The University of the West Indies, Mona Campus, Jamaica)

Abstract

Knowledge discovery and data-mining techniques have the potential to provide insights into data that can improve decision making. This paper explores the use of data mining to extract patterns from data in the domain of social welfare. It discusses the application of the Integrated Knowledge Discovery and Data Mining process model (IKDDM) a social welfare programme in Jamaica. Further, it demonstrates how the knowledge acquired from the data is used to develop a knowledge driven decision support system (DSS) in the PATH CCT programme. This system was successfully tested in the domain showing over 94% accuracy in the comparative decisions produced.

Suggested Citation

  • Ricardo Anderson & Gunjan Mansingh, 2014. "Data Mining Approach to Decision Support in Social Welfare," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 5(2), pages 39-61, April.
    • Handle: RePEc:igg:jbir00:v:5:y:2014:i:2:p:39-61
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