@article {10.3844/jcssp.2023.812.824, article_type = {journal}, title = {The Multistage Fuzzy Logic-Based Decision Support Model to Determine the Salary of New Employees}, author = {Perdana, Gregoryus Imannuel and Utama, Ditdit Nugeraha}, volume = {19}, number = {7}, year = {2023}, month = {Jun}, pages = {812-824}, doi = {10.3844/jcssp.2023.812.824}, url = {https://thescipub.com/abstract/jcssp.2023.812.824}, abstract = {Salary determination for prospective new employees is critical in determining the level of employee satisfaction that can motivate people. The goal of this research is to develop a decision support model to determine salaries for prospective new employees by combining three methods: Multistage fuzzy logic, and conventional and simple mathematical models. Fuzzy logic is used to calculate fuzzy parameters, while conventional methods are used to calculate non-fuzzy parameters by multiplying parameter values by their weights. In this study, data amounted to approximately 30 data obtained via a questionnaire, which describes the personal data of prospective new employees at a company. There are 18 parameters in this study divided into four main categories that determine the amount of salary for prospective new employees. This decision support model generates a salary for prospective new employees that the company can use as a reference when providing salaries.}, journal = {Journal of Computer Science}, publisher = {Science Publications} }