Enhancing Employee Performance Evaluation Application Using the Simple Additive Weighting (SAW) Method

Abstract

Accurate and objective employee performance evaluation remains a challenge for many organizations, often due to subjective assessments and a lack of standardized criteria. To address this problem, this study proposes the development of a web-based Decision Support System (DSS) utilizing the Simple Additive Weighting (SAW) method to support fair and transparent employee evaluations. The system was designed to assist the CV. Lestari Indojaya selects the best-performing employees based on multiple performance indicators, including job knowledge, work initiative, productivity and efficiency, communication, responsibility, discipline, and attendance. The SAW method, a widely used multi-criteria decision-making approach, was employed to calculate weighted scores for each employee, enabling systematic ranking and selection. The implementation of this system not only enhances the accuracy and objectivity of performance assessments but also motivates employees to improve their work quality. Overall, the proposed solution offers a data-driven, efficient, and transparent approach to evaluating employee performance.