Reward Decision Support System and Punishment on Food Companies Using MABAC Method

Abstract

The improvement of a company performances cannot be separated from the performance of each employee.
Periodic evaluation of employee performance becomes a routine task of the Human Resources General Affair
(HRGA) team that takes a long time and effort because it is still done manually. The results of employee
performance that have been assessed as a reference of determination of rewards and punishment. The
Decision Support System (DSS) is made with the aim of making it easier for HRGA to determine employee
rewards and punishments based on assessor factors that have been determined by the company. The criteria
chosen are attendance, loyalty and responsibility, work competency and work results (quality and quantity
results). The DSS methods that can be applied to this process is the Multi-Attributive Border Approximation
area Comparison (MABAC) Method. This method is used because consistent in solutions and expert for use
in logical decision making. The research data was taken from 11 samplings of bakery division employee
performance data for 1 year. Data is obtained from attendance and assessments from supervisors of each
division. The results of this research, is a decision support system web based in order to determine the
reward and punishment method using MABAC.