Implementation Of The K-Means Method In Grouping Districts And Cities In North Sumatra On Social Welfare Problems

Authors

  • Edisman Rahul Gonjales Siahaan STIKOM Tunas Bangsa

DOI:

https://doi.org/10.53842/jaiea.v1i2.86

Keywords:

Social Welfare Problems, Data Mining, K-Means, North Sumatra

Abstract

Social welfare problems are obstacles, difficulties or disturbances experienced by a person, difficulty or disturbance. or groups that cannot carry out their social functions and cannot establish harmonious and harmonious relationships with the surrounding environment. In this case, the problem of social welfare that the author does is in the province of North Sumatra which has 33 districts and cities. The source of this research data comes from the Central Bureau of Statistics of North Sumatra. The aim of this is to apply the k-means method in grouping districts and cities on social welfare issues that can help the government and social services in making decisions which areas should be dominantly assisted in solving social welfare problems in order to save costs. The k-means method is one of the methods in data mining to group data sets that are similar to others. The data are grouped into 3 clusters, namely high, medium and low clusters, the results of the high cluster are 2 regencies/cities, the medium cluster is 6 regencies/cities and the low cluster is 25 regencies/cities, these results can be a record for the local government and agencies in dealing with social welfare problems in regencies and cities in North Sumatra

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Published

2022-02-10

How to Cite

Edisman Rahul Gonjales Siahaan. (2022). Implementation Of The K-Means Method In Grouping Districts And Cities In North Sumatra On Social Welfare Problems. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 1(2), 168–173. https://doi.org/10.53842/jaiea.v1i2.86