Application of Fuzzy C-Means in Grouping Districts/Cities Based on Health Service Facilities in East Java

Authors

DOI:

https://doi.org/10.25139/inform.v3i2.1070

Keywords:

data mining, health facility, clustering, fuzzy c-means, sillhoute coefficient, purity

Abstract

Health is a very important thing for every human being because without good health, then humans will be difficult to do activities. We need health facilities that can support human health or society. This study discussed use of clustering algorithm in grouping districts or cities in East Java according to the number of health care facilities using Fuzzy C-Means. The data source of this research got from Central Bureau of Statistics of East Java. The cluster results obtained then validated with sillhoute coefficient and purity. With the centroid gained in the last iteration, four districts/cities were included in the first cluster, 26 districts/cities included in the second cluster, and 8 districts/cities included in the third cluster. The results of clustering validation is the value of sillhoute coefficient of 0.695 and the purity value of 1. This can be a suggestion to the East Java provincial government, districts / municipalities that are more concerned with having the number of health facilities based on the cluster that has been done.

Keywords— data mining; health facilities; clustering; fuzzy c-means; sillhoute coefficient; purity

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Published

2018-10-03

How to Cite

Application of Fuzzy C-Means in Grouping Districts/Cities Based on Health Service Facilities in East Java. (2018). Inform : Jurnal Ilmiah Bidang Teknologi Informasi Dan Komunikasi, 3(2), 62–68. https://doi.org/10.25139/inform.v3i2.1070

Issue

Vol. 3 No. 2 (2018)

Section

Volume 3 No. 2 2018

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