The Selection of Periodic Salary Increment of Civil Servants using Fuzzy MADM

Abstract

The Fuzzy Multi Attribute Decision Making (FMADM) methods used in this study are FSAW and FTOPSIS. They are developed for the selection of Periodic Salary Increment (KGB) for the Civil Servants (PNS) of the East Kalimantan province because there is a big possibility of an error in entering data, calculating salary and calculating the time of submission in manually. The FMADM method selects and ranks employees according to qualifications for salary increases based on a number of criteria that refer to government regulations. Criteria that are used as references for salary increment selection of civil servants are includes: years of experience, assessment of Employee Performance Target (SKP) for the past two years, behavioral assessment, and disciplinary penalty. Based on the results of 40 employees data used in this study, the accuracy is as much as 90% compared with reality for FSAW, and the accuracy of FTOPSIS is as much as 85% from reality. The minimum preference threshold value is 0.70 to pass the Periodic Salary Increment selection.