The Assessment Model to Rank Applicants for Research and Development Job Position in PT ABC

Abstract

Staff turnover has a negative impact on an organization's progress and development. Unfortunately, companies commonly experience difficulty replacing departing employees with qualified applicants that fit their job specifications. Staff turnover is influenced by the recruitment and selection process, and effective recruitment and selection reduce employee turnover, which boosts an organization's profitability. Therefore, organizations must consider getting competent people that fit the company's job specifications from the beginning of the recruitment process, demonstrating the importance of a well-organized and methodical hiring process. This article presents an assessment model to rank the applicants for research and development job positions in a company. The methods used in this model are the Fuzzy Analytical Hierarchy Process (F-AHP), Alfares' weighting method, and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS). The selection criteria for research and development job positions were classified into subjective, objective, and absolute factors and customized for PT ABC. The expert provided his judgments on the importance of the criteria in fuzzy pairwise comparisons, and the criterion weights were determined using F-AHP. The objective criteria weights were: education 0.039, working experience 0.083, analysis ability 0.274, research ability 0.290, and planning ability 0.312. At the same time, the subjective criteria weights were: interpersonal skills 0.267, software mastery 0.229, problem-solving ability 0.212, English fluency 0.053, and the weight of project management ability 0.239. The Alfares method will be used to weigh the sub-criteria. The criteria/sub-criteria and their weights will be used in the assessment model for ranking the candidates in the research and development job to rank potential applicants using the F-TOPSIS method.