Implementasi Metode SAW Dalam Pemilihan Supervisor Sewing Terbaik di PT. AAM

Abstract

Supervisor is a key position in the operational management of a company. The extensive responsibilities and high demands of the role contribute to stress levels, which can affect leadership effectiveness. Therefore, measures such as performance evaluations and incentive provision are implemented to enhance their competence, motivation, and productivity, as well as to recognize the workload they bear. This study aims to develop a web-based Decision Support System (DSS) application designed to assist company management in making more accurate and equitable decisions while improving the effectiveness of performance evaluations for sewing department supervisors. This research uses the Simple Additive Weighting (SAW) method due to its advantages in providing more accurate evaluations based on predetermined criteria values and preference weights. System testing using the Blackbox method demonstrated that the system functions well, with all tested features and functionalities meeting the expected specifications. The research findings identified one alternative with the highest evaluation score, Alternative A27, achieving a vector value of 94.6, outperforming the second-ranked alternative, A19, with a vector value of 89.4 by a margin of 5.2. This emphasizes that the decision support system using the SAW method is capable of providing recommendations based on calculations aligned with the established evaluation criteria, supporting decision-making in selecting high-quality sewing supervisors aligned with the company's needs.