<![CDATA[Scholarships play a vital role in supporting high-achieving students who face financial constraints. However, the selection process is often time-consuming and prone to subjectivity. This study develops a predictive model for scholarship recipients using the Artificial Neural Network (ANN) approach to create a more efficient and objective selection system. The dataset includes academic performance, parental income, number of dependents, and non-academic achievements. The ANN model is designed through data preprocessing, training, and evaluation stages, using metrics such as accuracy, precision, recall, and F1-score. The results indicate that ANN can accurately and effectively predict scholarship recipients, making it a valuable tool to assist decision-making in scholarship distribution.]]>
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