<![CDATA[The Stabat Religious Court faces challenges in grouping the annual data on marriage dispensation applications. This data has not been optimally utilized to generate information that can support decision-making in understanding age patterns, causal factors, and areas of residence with the highest application rates. This study aims to analyze age patterns and causal factors of marriage dispensation using data mining methods with the K-Means Cluster algorithm. Determining the optimal number of clusters was carried out using the Elbow method through analysis of the Sum Of Squared Error (SEE) value, which indicated the optimal number of clusters was 3 clusters. A total of 749 marriage dispensation application data from 2021–2025 were analyzed using the Knowledge Discovery in Database (KDD) stages, which include data selection, data preprocessing, transformation, data mining (cluster), and evaluation with the help of MATLAB. The variables used in this study include the applicant's age, the reason for the marriage dispensation application, and the applicant's area of residence. The results of this study indicate that the k-means algorithm using the elbow method is capable of systematically grouping marriage dispensation data based on similar characteristics. The clustering results provide information on age patterns, causal factors, and domiciles of marriage dispensation applicants, thus providing recommendations for stabat religious courts in formulating policies and efforts to prevent early marriage.]]>
Copyrights © 2026
