Comparison of Cluster Ensemble and Two Step Cluster Methods on Clustering with Mixed Type Data

Authors(3) :-Fera Hermawati, Budi Susetyo, Agus Mohamad Soleh

Health development is supported by the availability of adequate health facilities and personnel. To facilitate the government in determining the policies taken, it is necessary to group the region to know which areas that need improvement in health facilities and personnel. Cluster analysis is used to group objects based on certain characteristic similarities. Cluster analysis is generally applied to objects with numerical data types. Health facility and health personnel data have categorical and numerical types or also called mixed data type, so it is necessary to use clustering for mixed types data. This study aims to compare cluster ensemble method and two step cluster method in clustering mixed type data. The comparative criterion used is the ratio between diversity within cluster (S_w) and the diversity between cluster (S_b). Smaller ratio values indicate a better method. The research results showed that cluster ensemble method is a better method than the two step cluster method in clustering mixed type data.

Authors and Affiliations

Fera Hermawati
Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia
Budi Susetyo
Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia
Agus Mohamad Soleh
Department of Statistics, Bogor Agricultural University, Bogor, West Java, Indonesia

Clustering, Cluster Ensemble, Two Step Cluster, Mixed Type Data

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Publication Details

Published in : Volume 4 | Issue 9 | July-August 2018
Date of Publication : 2018-07-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 135-141
Manuscript Number : IJSRSET184932
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Fera Hermawati, Budi Susetyo, Agus Mohamad Soleh, " Comparison of Cluster Ensemble and Two Step Cluster Methods on Clustering with Mixed Type Data, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 9, pp.135-141, July-August.2018
URL : http://ijsrset.com/IJSRSET184932

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