<![CDATA[The process of reporting marriages at the Religious Affairs Office (KUA) in Laubaleng District is still done manually, which results in obstacles in the management, accuracy and efficiency of data access. This research aims to overcome this problem through developing a system based on the K-Means clustering method. This system is designed to group marriage reporting data based on attributes such as age, marital status, and month of marriage, so as to provide a more structured and informative data pattern. The Elbow method is used to determine the optimal number of clusters, while the K-Means algorithm is applied using Euclidean distance to calculate the closeness of the data to the centroid. The research process involves collecting reporting data from 2019 to 2024, data preprocessing, normalization, and evaluating clustering results using the Davies-Bouldin Index (DBI). The research results show that the K-Means method is effective in grouping data, providing clear visualization of the distribution of marriage patterns, and increasing the efficiency of data management at KUA. With this system, KUA can increase access speed, reduce the potential for errors, and support more accurate data-based decision making.]]>
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