Decision Support System with Simple Additive Weighting for Recommending Best Employee - Painem Painem; Hari Soetanto (Proceeding of the Electrical Engineering Computer Science and Informatics, 2019)
Human resources are significant assets in an organization. To increase work motivation for employees, various strategies are needed, such as giving rewards to employees who excel, giving sanctions to employees who break the rules and training employees. Rewarding for employees at Universitas Budi Luhur (UBL) is still based on the subjective assessment of the leadership. Determination of employees who perform well also has not been based on standard criteria or assessment. Therefore, in this study, a decision support system was developed to conduct the best employee assessment and selection. This study uses the Simple Additive Weighting (SAW) method. The SAW method was chosen because it was able to select the best alternative from several alternatives. Determination of the best employees using nine criteria, namely discipline, appearance, achievement, interpersonal skills, the ability to provide input, does not cause problems, ability to cooperate, coordination skills, and motivating abilities. The test results using the ISO-9126 model for web-based DSS applications developed in this study indicate that the quality of applications is 81%, which means that the criteria are excellent.