Decision Support System for Performance Assessment of Honoray Personnel Applying MABAC, MOORA, and ARAS Method with a Combination of ROC Weighthing

Abstract

MABAC (Multi-Attributive Border Approximation area Comparison), ARAS (Additive Ratio Assessment), and MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) are decision support system methods employed for evaluating the performance of honorary staff. MABAC utilizes a multi-attribute border approximation area approach to measure the relative performance of honorary staff. ARAS assigns weights to competing attributes and produces assessment ratio values aiding in decision-making. Meanwhile, MOORA focuses on multi-objective optimization by considering ratio analysis. The combination of these three methods provides a holistic and comprehensive framework for assessing the performance of honorary staff, enabling decision-makers to effectively evaluate their contributions and achievements based on predefined criteria. This approach allows for the determination of relative rankings and the selection of honorary staff that best align with organizational needs