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The study aims to analyze the effectiveness of adaptive learning systems based on artificial intelligence (AI) in improving student learning motivation. The study focused on three main aspects: student learning motivation levels, the effectiveness of adaptive learning systems, and the factors that influence the efficiency of these systems. The study used a survey method with a questionnaire instrument distributed to students using an AI-based adaptative learning system. The data collected were analyzed using descriptive statistics to describe the level of motivation for learning, the system's efficiency, and factors influencing it. AI-based adaptive learning systems are effective in providing material that matches students' abilities, providing helpful feedback, and adapting learning methods to individual learning styles. Furthermore, factors such as the availability of technology facilities, the ability to use technology, academic support, the quality of materials, and the flexibility of learning times play an important role in improving the efficiency of the system. Therefore, AI-based adaptive learning systems are effective in increasing student learning motivation. The system provides a personalized and responsive learning experience to individual needs, thereby enhancing students' understanding, confidence, and learning spirit. To ensure optimal efficiency, there is a need for improvements in technology facilities, training for students and lecturers, as well as the development of quality materials