Decision Making Model for Best Employee Evaluation Using Integration of ROC and MOORA Methods

Abstract

Employee evaluation is an important aspect in human resource management because it is related to awarding rewards, career development, and increasing company productivity. However, the manual assessment process is often influenced by subjectivity, resulting in less than optimal results. This study aims to apply a combination of the Rank Order Centroid (ROC) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) methods as a decision support system in determining the best employees. The ROC method is used to obtain the weight of each criterion based on its order of importance, while the MOORA method is used to normalize, weight, and calculate preference values ​​to obtain an alternative ranking order. This study uses four assessment criteria, namely performance, discipline, attendance, and absenteeism, involving ten employees as alternatives. The results of the weighting using the ROC method produce a weight of 0.5208 for the performance criterion, 0.2708 for discipline, 0.1458 for attendance, and 0.0625 for absenteeism. Furthermore, the ranking results using the MOORA method showed that alternative A7 received the highest preference score of 0.327, followed by A3 with 0.308 and A9 with 0.305. The research findings indicate that the integration of the ROC and MOORA methods can produce a more objective, measurable, and consistent evaluation process, thus serving as a basis for supporting decision-making in identifying the best employees in a company.