The implementation of the Merdeka Curriculum in Indonesia provides flexibility for students to select learning paths based on their personal interests and competencies. However, in practice, the class streaming system at SMAN 1 Sambit still relies heavily on academic grades processed through spreadsheets, which often leads to inaccuracies, inconsistencies, and subjective decision-making. This study aims to develop a web-based decision support system (DSS) for class streaming using the Simple Additive Weighting (SAW) algorithm. Three main criteria are considered: students’ subject interest, character assessment, and academic achievement, with respective weights of 40%, 40%, and 20%. Data were collected from 126 students of grade X in the academic year 2024/2025. The research method consisted of requirement analysis, system design, algorithm implementation, and black-box testing. The SAW algorithm was applied through stages of decision matrix construction, normalization, weighting, and preference score calculation to generate a ranking of class recommendations. The results indicate that the system provides accurate, objective, and transparent recommendations, significantly reducing misplacement compared to the conventional method. Validation results showed a high level of consistency between the system’s recommendations and the school’s manual validation. Furthermore, black-box testing confirmed that all system functionalities operated as expected. This study highlights the potential of SAW-based DSS in supporting effective implementation of the Merdeka Curriculum. However, the limitation of this study lies in the use of a single algorithm. Future research is suggested to compare SAW with other MADM methods such as AHP or TOPSIS for further optimization.
Keywords: Class Placement, Decision Support System, SAW Algorithm