Analisa Penerapan Metode WASPAS Dalam Sistem Pendukung Keputusan Penilaian Kinerja Checker Terbaik Pada Kereta Api - Imam Purwanto (Bulletin of Computer Science Research, 2023)
Performance assessment in a work environment involving monitoring and checking activities plays an important role in maintaining quality and efficiency. This study analyzes the application of the Weighted Aggregated Sum Product Assessment (WASPAS) method as part of the Decision Support System in the process of evaluating the performance of the best checkers. The WASPAS method is used to address the complexity of measuring checker performance by considering various relevant criteria. This article describes the steps for implementing the WASPAS method and its integration into a decision support system. The results of the analysis show that this approach can help improve accuracy and objectivity in performance appraisal, providing a strong basis for management to make informed decisions regarding the selection of the best checkers. In this study, checker performance data were collected and analyzed carefully. The results of the analysis provide insight into a more accurate and objective checker performance assessment. The integration of the WASPAS method into DSS helps managers or decision makers overcome subjectivity in the assessment process, as well as avoid potential bias that could affect the final result. From the results of the study, it can be concluded that the application of the WASPAS method in SPK can increase the validity and reliability of checker performance assessments. This approach allows managers to carry out a more comprehensive and balanced evaluation of every aspect of checker performance. However, careful selection of criterion weights and sensitivity to changes in weights is required to ensure optimal results. Thus, this study provides a more in-depth look at how the WASPAS method can be applied in the DSS context for assessing the performance of the best checkers. The implications can be felt in making decisions that are more informed and accurate in managing individual performance in the work environment. From the results of calculations that have been carried out from 7 alternative Checker data using the WASPAS Method, the best alternative, namely the fifth alternative with the name Riski Sudrajat, obtains the highest score, namely 0.939. Therefore the fifth alternative was chosen as the Checker with the best performance on the Railway.