Design of a Fuzzy Mamdani Based Decision Support System for Fair Wage Determination of Palm Oil Workers - Zuheri Lubis; Sriani Sriani (Electronic Journal of Education, Social Economics and Technology, 2025)
Wage determination in palm-oil plantations often relies on subjective assessments, which may lead to inconsistencies, unfair practices, and disputes between workers and management. To address this issue, this study proposes the application of the Fuzzy Mamdani method as a decision support system for determining plantation workers’ wages. The main objective is to design and implement a fuzzy-based model that provides fair and transparent wage recommendations by integrating multiple worker performance criteria. The research was conducted at PT CSIL with a sample of 45 workers. Four key variables length of service, attendance, overtime, and work performance were formulated into linguistic variables with triangular membership functions. A fuzzy rule base, developed in collaboration with domain experts, was used to perform Mamdani inference with centroid defuzzification. Data were obtained from company records and validated using comparisons with the actual wage distribution determined by the payroll department. The results show that the system recommendations were consistent with the company’s wage decisions for 40 out of 45 workers, representing an agreement rate of 88.9%. This demonstrates that the Fuzzy Mamdani method can effectively reduce subjectivity and improve fairness in wage determination. In conclusion, the proposed system provides a reliable tool to support payroll decision-making in plantation settings. The implications suggest that broader adoption of fuzzy-based models can enhance transparency and worker satisfaction in agricultural wage systems.