@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}
}