METODE K-MEANS UNTUK PENGELOMPOKAN MASYARAKAT MISKIN DENGAN MENGGUNAKAN JARAK KEDEKATAN MANHATTAN CITY DAN EUCLIDEAN (STUDI KASUS KOTA BINJAI)

Abstract

The occurrence of poverty in the community is caused by the inability of the family head economically to meet the primary needs of family members, namely clothing, food, shelter, health, and education needs. The poor are almost present in every country, city, and region, this becomes a common problem. The current poverty data obtained from the Binjai City Central Bureau of Statistics is from 2012, and the number of poor people has increased in 2016 by 17,800 people with a poverty line (Rp. /Cap/month) of Rp. 343,078 and the latest data obtained in 2017 were 18,230 people with Poverty Lines (Rp. / Kap / Bulan) Rp. 371,387. In the database of the Binjai City Central Bureau of Statistics there are very diverse data on the poor, with this data, researchers try to explore data from the poor city of Binjai to obtain new information by grouping poverty data using the k-means clustering data mining method using distance the closeness of Manhattan City and Euclidean, so that groups of variables that are very influential in the community of poverty can be identified. The observed variables such as the level of education of the household head, education level of housewives, employment, number of family members, and other observed variables affect poverty. And the results of the k-means method for grouping poor people using proximity to Manhattan city and euclidean that can provide additional information in optimizing poverty alleviation in the city of Binjai.