Design and Construction of a Decision Support System for Teacher Performance Assessment Using the Simple Additive Weighting Method (Case Study: SMAN 2 Sumenep)

Teacher performance assessment is a crucial factor in improving the quality of education; however, the manual system still used at SMAN 2 Sumenep is considered subjective, slow, and prone to errors. This study aims to design a web-based decision support system to evaluate teacher performance more objectively and efficiently using the Simple Additive Weighting (SAW) method, which was chosen for its simple and effective algorithm in multi-criteria decision-making and its ability to generate clear rankings based on the weight of each criterion. The study employed 28 assessment criteria and involved 88 teachers selected through purposive sampling, with data collected through observation, interviews, and documentation within the school environment. The system receives input from evaluators, performs normalization, calculates preference values, and generates performance rankings. The implementation results showed that the system accelerated the assessment process, increased transparency, reduced bias in decision-making, and improved evaluation accuracy by up to 80%, making it an effective tool for evaluating and enhancing teacher quality at SMAN 2 Sumenep.