This research endeavors to revolutionize the process of employee performance evaluation and bonus allocation within organizational settings by introducing a sophisticated Decision Support System (DSS) underpinned by the Analytical Hierarchy Process (AHP). The study delves into the development, implementation, and testing phases of the DSS, aiming to enhance objectivity, fairness, and efficiency in decision-making methodologies. The research commences with an exploration of existing challenges in performance evaluation systems, acknowledging the subjectivity and limitations prevalent in traditional methods. The conceptual framework outlines the hierarchical structure of the DSS, encompassing diverse performance criteria and sub-criteria essential for a comprehensive evaluation. Implementation involves the integration of the AHP method into the DSS, facilitating precise pairwise comparisons, priority vector calculations, and weighted score determinations. Rigorous testing and validation phases ascertain the system's accuracy, consistency, and responsiveness in evaluating employee performance and aligning bonus allocation with contributions. Results from the testing phase illuminate the DSS's efficacy, showcasing its ability to provide transparent and data-driven evaluations, fostering fairness, trust, and intrinsic motivation among employees. The implications of employing this DSS extend beyond bonus allocation, influencing organizational performance, decision-making, and the broader organizational climate.
                        
                        
                        
                        
                            
                                Copyrights © 2024