Research Article Open Access

Decision Support Model for Employee Selection Based on Data Mining and Fuzzy Logic

Clarissa Elfira Amos Pah1 and Ditdit Nugeraha Utama1
  • 1 Bina Nusantara University, Indonesia
Journal of Computer Science
Volume 16 No. 5, 2020, 686-701

DOI: https://doi.org/10.3844/jcssp.2020.686.701

Submitted On: 22 January 2020 Published On: 4 June 2020

How to Cite: Pah, C. E. A. & Utama, D. N. (2020). Decision Support Model for Employee Selection Based on Data Mining and Fuzzy Logic. Journal of Computer Science, 16(5), 686-701. https://doi.org/10.3844/jcssp.2020.686.701

Abstract

This paper explains the use of data mining and fuzzy logic in optimizing decision making for employee recruitment, especially in IT Consultant company. This method addresses the company's need to recruit employees with more objective and accurate by utilizing historical data to find patterns of potential employees for the company. First, classification will be carried out using data mining to determine the predictor attributes of potential employees. These predictor attributes will then be used to arrange fuzzy rule base and fuzzy logic structure which will be used to prioritize employees to be accepted. The results obtained will prioritize employees who are recruited objectively scientifically.

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Keywords

  • Data Mining
  • Fuzzy Logic
  • Decision Support
  • Employee Recruitment