@article{(Open Science Index):https://publications.waset.org/pdf/11782,
	  title     = {Knowledge Discovery Techniques for Talent Forecasting in Human Resource Application},
	  author    = {Hamidah Jantan and  Abdul Razak Hamdan and  Zulaiha Ali Othman},
	  country	= {},
	  institution	= {},
	  abstract     = {Human Resource (HR) applications can be used to
provide fair and consistent decisions, and to improve the
effectiveness of decision making processes. Besides that, among
the challenge for HR professionals is to manage organization
talents, especially to ensure the right person for the right job at the
right time. For that reason, in this article, we attempt to describe
the potential to implement one of the talent management tasks i.e.
identifying existing talent by predicting their performance as one of
HR application for talent management. This study suggests the
potential HR system architecture for talent forecasting by using
past experience knowledge known as Knowledge Discovery in
Database (KDD) or Data Mining. This article consists of three
main parts; the first part deals with the overview of HR
applications, the prediction techniques and application, the general
view of Data mining and the basic concept of talent management
in HRM. The second part is to understand the use of Data Mining
technique in order to solve one of the talent management tasks, and
the third part is to propose the potential HR system architecture for
talent forecasting.},
	    journal   = {International Journal of Industrial and Manufacturing Engineering},
	  volume    = {3},
	  number    = {2},
	  year      = {2009},
	  pages     = {178 - 186},
	  ee        = {https://publications.waset.org/pdf/11782},
	  url   	= {https://publications.waset.org/vol/26},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 26, 2009},
	}