Building a qualitative recruitment system via SVM with MCDM approach

Abstract

Advances in information technology have led to behavioral changes in people and submission of curriculum vitae (CV) via the Internet has become an often-seen phenomenon. Without any technological support for the filtering process, recruitment can be difficult. In this research, a method combining five-factor personality inventory, support vector machine (SVM), and multi-criteria decision-making (MCDM) method was proposed to improve the quality of recruiting appropriate candidates. The online questionnaire personality testing developed by the International Personality Item Pool (IPIP) was utilized to identify the personal traits of candidates and both SVM and MCDM were employed to predict and support the decision of personnel choice. SVM was utilized to predict the fitness of candidates, while MCDM was employed to estimate the performance for a job placement. The results show the proposed system provides a qualified matching according to the results collected from enterprise managers.