ANALISIS CLUSTER MENGGUNAKAN ALGORITMA K-MEANS CLUSTER UNTUK CULSTERING JENIS PENYAKIT MENULAR PADA PUSKESMAS DI KECAMATAN KOTA TANGERANG - Aninda Rachma; Aden Aden; Yulianti Rusdiana (JURNAL SAINTIKA UNPAM, 2019)
The research in this paper aims to cluster the types of diseases in the sub-district Puskesmas in the city of Tangerang, to facilitate the handling and improvement of the environment, and to find out which disease is the most dominant in each cluster, during clustering at the sub-district Puskesmas in Tangerang City. The subject of this research is the result of clustering of infectious diseases with the method used is Cluster Analysis using the K-means Cluster Algorithm using calculations using SPSS 22. And the results of this study can find out the type of disease with each Puskesmas according to the sub-district, for which clusters are determined there are four clusters where each cluster is a type of infectious disease itself, namely pulmonary Tuberculosis, pneumonia, dengue, and diarrhea, for each cluster each divided according to its sub-district or Puskesmas. With these results, it can be concluded that the clustering results know which sub-districts have contracted infectious diseases according to the cluster formed.