<![CDATA[This research examines the application of rule-based Artificial Intelligence (AI) to address demographic data inconsistency among prospective students at SD Al-Imam Islamic School. Unstructured applicant data, particularly in the village/sub-district address column, often impedes efficient analysis and strategic decision-making. By implementing a dictionary-based normalization technique (normalizationMap) using Google Apps Script, this study aims to enhance data quality and minimize input inconsistencies. The role-based approach ensures that various input formats are mapped to a predefined standard. The implementation results demonstrate a significant improvement in the accuracy of the address data, directly supporting more precise demographic visualization. This practical and effective AI solution facilitates data-driven decision-making for future student enrollment strategies, showcasing a tangible contribution to data management within a limited-resource educational environment.]]>
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