Decision Support System for Determining Employee Income Tax Using the Fuzzy Sugeno Method at BMKG North Sumatra Region

Abstract

Accurate, consistent, and efficient calculation of employee income tax is essential due to the involvement of multiple components, including basic salary, allowances, deductions, and employee status. Manual calculation increases the risk of errors and requires significant time. This study aims to design a decision support system for determining employee income tax at the BMKG Regional Office of North Sumatra using the Fuzzy Sugeno method. The Fuzzy Sugeno method is selected for its ability to process both numerical and linguistic data through fuzzy rules, enabling more flexible and measurable decision-making. A quantitative approach is employed, encompassing problem identification, data collection, design of input and output variables, formation of fuzzy sets, formulation of inference rules, and system testing. The input variables include base salary, allowances, deductions, and dependent status, while the output is the calculated employee income tax. The anticipated result is a decision support system that enables the agency to determine employee income tax more rapidly, accurately, and consistently. Therefore, the Fuzzy Sugeno method is positioned as an effective solution to support decision-making processes at the BMKG Regional Office of North Sumatra.