Implementation of the Mamdani Fuzzy System as a Decision Support for Contract Extensions for Non-Staff Employees in Manufacturing Companies

Abstract

This study applies the Mamdani Fuzzy method as a decision support system in determining the feasibility of contract extension for non-staff employees in a manufacturing company. Performance assessment is conducted based on seven criteria, namely Attendance (C1), Work Quality (C2), Discipline (C3), Teamwork (C4), Initiative (C5), Responsibility (C6), and Professional Attitude (C7). The assessment uses the company's official linguistic scale: Very Poor (1), Poor (2), Sufficient (3), Good (4), and Very Good (5). Based on company regulations, employees with a total performance score below 23 are declared to have their contracts discontinued (termination), while employees with a score ≥ 23 are entitled to a contract extension or be appointed as permanent employees. The dataset consists of 40 non-staff employees from ten departments. The fuzzy inference process includes fuzzification, rule base formation, min-max inference, and centroid defuzzification. The results showed that 11 employees (27.5%) were recommended to have their contracts terminated, 16 employees (40.0%) were recommended to have their contracts extended, and 13 employees (32.5%) were recommended to be appointed as permanent employees. This system has proven to be able to produce recommendations that are objective, transparent, and in line with official company regulations.