Clustering of Women's Family Planning Contraceptive Use Data Using the Clustering Method at the Population Control and Family Planning Office

Abstract

The Department of Population Control and Family Planning (DPPKB) of Binjai City is a government institution responsible for implementing the Family Planning (KB) Program to improve family welfare and control population growth. The increasing amount of contraceptive usage data each year requires an appropriate data processing method to generate information that supports decision-making. This study aims to apply the K-Means Clustering algorithm to classify contraceptive usage data among women of reproductive age based on age, contraceptive method, and region. The research method includes transforming the data into numerical form, performing the clustering process using three clusters (K = 3), and implementing the system using MATLAB. The results show that the K-Means Clustering algorithm successfully groups the data into three clusters based on the similarity of their characteristics. The clustering results provide information on contraceptive usage patterns according to age, contraceptive method, and region, which can support the Department of Population Control and Family Planning of Binjai City in evaluating, formulating policies, and planning Family Planning programs more effectively and accurately.