Normalisasi Data Kependudukan Dengan Model Min Max Dan Algoritma K-Means Untuk Pengelompokkan Tingkat Ekonomi Masyarakat


  • Wenny Wenny * Mail Universitas Budi Darma, Medan, Indonesia
  • (*) Corresponding Author
Keywords: Disdukcapil; KTP; Clustering; K-Means Algorithm

Abstract

Desidential data at Disdukcapil Deli Serdang has only been used for administrative purposes such as making certificates, ID cards, family cards, and others. Meanwhile, the data should be able to increase its usefulness functions such as classifying the economic level of the Deli Serdang Regency community. So far, many people feel disadvantaged because the distribution of government assistance to low-level economic communities is often misdirected, there are people who should get assistance but instead cannot, but there are people who are less deserving of assistance who can get assistance, this can be influenced by various factors such as kinship, closeness or other things. techniques are needed in classifying the economic level of the Deli Serdang Regency community based on certain criteria. The K-Means algorithm is one of the algorithms in data mining to classify certain data, for that it is very suitable to use the K-Means algorithm in classifying the economic level of the community.

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Published: 2024-04-29
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