Abstract— Poverty is a condition of life that is understaffed
by a person or household so that it is unable to meet the
minimum or proper needs for his or her life. The poverty Data in
each region will differ. It is influenced by many of its supporting
indicators. By determining and measuring the indicators of
poverty, it will facilitate and recognize the poverty level of the
region. Grouping characteristics of a region based on poverty
indicators, so that the government can precisely and quickly take
policies to mitigate poverty in a region. The method used in this
study uses the K-Means Clustering method. The Clustering
method is selected because this method has the ability to classify
large amounts of data with faster process times efficiently. The
object in this study used data published by the BPS (Badan Pusat
Statistik) on poverty Data and information in the Regency/city in
2018. Based on the results of this study, the results of the
characteristic mapping of each group formed based on the
highest and lowest value of poverty indicator of West Java
province year 2018. With the characteristics found in each
region, it will certainly be a solid foundation for government
organizers to provide the right and quick policy/approach to
overcome the poverty that is found in the region.