IMPLEMENTASI ALGORITMA K – NEAREST NEIGHBORUNTUK MENGKLASIFIKASIKAN FAKTOR PERNIKAHAN DINI - Siti Muntari; Febriansyah Febriansyah (UNIVERSITAS STEKOM, 2026)
Early Marriage in Pagar Alam City is currently still quite high, the Pagar Alam Religious Court only relies on a recap of the number of cases per year to draw conclusions about the early marriage data. This method has limitations in classifying early marriage factors, so the Religious Court has difficulty in monitoring and controlling the occurrence of Early Marriage in Pagar Alam City. The purpose of this research thesis is to produce a classification system for Early Marriage factors using the K-Nearest Neighbor Algorithm to find out what factors influence the occurrence of Early Marriage, the method used in this study is the Cross Industry Standard Process for Data Mining (CRISP-DM) which has 6 stages, namely: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The testing stage in this study uses Confusion Matrix and BlackBox Testing. The final results of this study indicate that the system can classify Early Marriage factors. The classification model built achieved an Accuracy of 94.12% and a Precise value of 85.71% and a Recall value of 100.00%, while testing using Black Box testing in the form of alpha obtained a feasibility value of 83.2%, so this system is very suitable for use.