World Map Asia clustering using Agglomerative Clustering Algorithm
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clustering,
data mining
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Abstract
Cluster analysis is one technique that can be correlated. Explain the closeness or similarity between objects and variables. The analysis is divided into 2 methods, namely hierarchical and non-hierarchical. In the hierarchical method, there are several methods, including the complete linkage method, average linkage, single linkage and ward linkage. This method is applied in the grouping of the Asian continent. The purpose of this study is to classify countries based on GDP and population in Asia. In this study, the hierarchical method used is Agglomerative Hierarchical Clustering (AHC). 177 countries with 6 columns of country data around the world and sorted into 47 country data columns and 6 country data columns in the Asian continent. The per capita state income is obtained by dividing GDP by population. Then made 4 clusters. Cluster 1 consists of the United Arab Emirates, Kuwait and Qatar. Cluster 2 consists of Brunei, Oman, Saudi Arabia and Taiwan. Cluster 3 consists of 34 countries and the last cluster is Cyprus, Israel, Kazakhstan, South Korea, Malaysia.
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