<![CDATA[The quality of teacher performance evaluation plays an important role in improving educational outcomes, yet conventional assessment approaches often suffer from subjectivity, inconsistency, and lack of transparent weighting mechanisms. This study proposes a Decision Support System (DSS) model by integrating the LODECI method for objective criteria weighting and the CODAS method for alternative ranking to produce more accurate and data-driven evaluation results. The LODECI method determines criterion weights based on data distribution characteristics, resulting in proportional weights where Classroom Management (0.1881), Pedagogical Competence (0.1825), and Creativity and Innovation (0.1702) are identified as the most influential criteria. Furthermore, the CODAS method evaluates teacher performance using a distance-based approach to the negative ideal solution, producing preference values that enable clear differentiation among alternatives. The ranking results show that A7 – Gina achieves Rank 1 with a value of -0.2399, followed by A3 – Citra in Rank 2 with -0.2181, and A9 – Intan in Rank 3 with -0.1374, indicating their superior performance compared to other alternatives. To ensure robustness, a sensitivity analysis was conducted using 18 threshold (φ) scenarios ranging from 0.1 to 0.95. The results demonstrate that the top-ranked alternatives (A7, A3, and A9) consistently maintain their positions across all scenarios, indicating that the proposed model is stable and not significantly affected by parameter changes. Therefore, the integration of LODECI and CODAS within a DSS framework proves to be effective in producing objective, consistent, and reliable teacher performance evaluations that can support decision-making in educational institutions.]]>
