Classification Techniques for Talent Forecasting in Human Resource Management

Authors:
Hamidah Jantan;Abdul Razak Hamdan;Zulaiha Ali Othman
Affiliations:
Faculty of Computer Science and Mathematics, Universiti Teknologi MARA (UiTM) Terengganu, Dungun, Malaysia 23000 and Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia ( ...;Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, Malaysia 43600;Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi, Malaysia 43600
Venue:
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Year:
2009

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Abstract

Managing an organization's talents, especially in assigning the right person to the right job at the right time is among the top challenge for Human Resource (HR) professionals. This article presents an overview of talent management problems that can be solved by using classification and prediction method in Data mining. In this study, talent's performance can be predicted by using past experience knowledge in HR databases. For experiment purposes, we used the possible classification and prediction techniques in order to find out the suitable techniques for HR data. An example demonstrates the feasibility of the suggested classification techniques using selected employee's performance data. Finally, the initial experiment results show the potential classification techniques for talent forecasting in Human Resource Management (HRM).