<![CDATA[This study explores the potential of Artificial Intelligence (AI) in optimizing scholarship allocation processes within Indonesia's higher education system. The research highlights the challenges faced in the traditional scholarship distribution methods, including inefficiencies and biases, which hinder equitable access to educational opportunities for underprivileged students. By employing a systematic literature review (SLR) using the PRISMA methodology, the study investigates various AI techniques, including K-Nearest Neighbors, Naive Bayes, Decision Trees, and Fuzzy Logic, to improve the accuracy and efficiency of scholarship selection. The findings demonstrate that AI-driven approaches can enhance transparency, fairness, and resource allocation, aligning with the Sustainable Development Goals (SDGs), particularly SDG 4 (Quality Education) and SDG 10 (Reduced Inequalities). The integration of AI can help optimize government programs like KIP Kuliah, ensuring that scholarships are awarded to the most deserving candidates. However, challenges such as improving data quality, model selection, and ensuring fairness and transparency in decision-making remain. Future research should focus on addressing these challenges, exploring more advanced AI techniques, and assessing the long-term impact of AI-driven scholarship allocation on educational outcomes and social mobility in Indonesia.]]>
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