Intelligent Techniques for Decision Support System in Human Resource Management

Nowadays, the evolution of information technology applications makes it an absolute obligation on behalf of the decision makers to continuously make the best decisions in the shortest possible time. Decision Support System (DSS) is a technology and application that assists managerial decision makers utilizing data and models to solve semi-structured and unstructured problems (Qian et al., 2004). This chapter discusses general issues on DSS technologies and an idea to apply DSS technologies into Human Resources Management (HRM) field. Recently, the collaboration between DSS technologies and Artificial Intelligent techniques has produced another type of DSS technology known as Active DSS, it is a technology that will take place in the new millennium era (Shim et al., 2002). Active DSS is an outcome of new DSS technologies and also known as a part of Intelligent System applications. Active DSS applications such as Expert System, Knowledge-based System, Adaptive DSS and Intelligent Decision Support System (IDSS) are categorized as part of Intelligent System studies. Expert systems technology, which was a crucial area for enterprise capital in 1985-1990, is now being replaced by the intelligent system applications (Faye et al., 1998). Intelligent systems are developed to fulfill the two main functions. Firstly, to screening, shifting and filtering the increasing overflow of data, information and knowledge. Secondly, as a supporter of an effective and productive decision making that is suitable to the user needs. Intelligent systems can be developed for these purposes; range from self-organizing maps to smart add-on modules to make the use of applications more effective and useful for the users (Shim et al., 2002). Human is important and a very valuable asset for an organization and managed by Human Resource professional. HRM system is an important element in the success of an organization, known as an integrated and interrelated approaches to managing human resources (DeNisi & Griffin, 2005). Activities in HRM involve a lot of unstructured processes such as staffing, training, motivation and maintenance (DeCenZo & Robbins, 2005). Besides that, decision making for unstructured processes in HRM usually depends on human judgment and preference. However, human decisions are subject to the limitation because sometimes people forget the crucial details of the problem, and besides, fairness and