Abstract

Welfare and poverty in an area are two things that are interrelated and affect each other. The increasing number and density of the population also have the potential to increase social problems and the level of welfare of the population. This has an effect on reducing job opportunities and growing family needs, which can increase the number of pre-prosperous families in Pekalongan City. The clustering of pre-prosperous, prosperous1, and prosperous families aims to determine the mapping of their distribution so that they can be used as material for decision-making and policies of related agencies. The method used to perform this clustering is the K-Means algorithm which emphasizes the data center of each cluster. The mapping results show that there are 10 urban villages that fall into cluster 1, 3 villages that fall into cluster 2, 11 villages that fall into cluster 3, and 3 villages that fall into cluster 4.

Keywords: Pre-prosperous families, prosperous families, clustering, K-Means, Pekalongan City