Decision Support System for Determining Effective Learning Strategies for Students Using the SMART Method

Abstract

Effective learning strategies are essential factors in improving students’ academic achievement. However, at SMP Negeri 2 Binjai, several challenges remain, including the low effectiveness of applied learning methods, the lack of adaptation to individual learning styles, and the limited use of academic data in supporting learning decisions. These issues were further exacerbated by the post-pandemic shift toward hybrid learning models, which has not been fully optimized. To address this problem, this study designed a Decision Support System (DSS) using the SMART (Simple Multi-Attribute Rating Technique) method to recommend suitable learning strategies for students. The system was developed through stages of requirement analysis, logical design of the SMART calculation, and the implementation of integrated multi-criteria processing. The results show that the system can provide objective and accurate learning strategy recommendations. From 32 students analyzed, 11 students (34.37%) were recommended to adopt E-learning, 7 students (21.87%) to use Blended Learning, and 14 students (43.75%) to apply Traditional Learning. The highest score of 1.00 was achieved by two students in the E-learning category, while the lowest score of 0.125 was recorded in the Traditional category. These findings confirm that the application of the SMART method in DSS is effective in helping teachers and students determine more adaptive and personalized learning strategies, thereby supporting the improvement of learning quality in schools.