Regional Clustering Based On HDI Components In Indonesia

Authors

  • Azlam Nas  Department of Economics, IPB University, Bogor, Indonesia
  • Sri Mulatsih  Department of Economics, IPB University, Bogor, Indonesia
  • Muhammad Findi   

DOI:

https://doi.org/10.32628/IJSRSET21813

Keywords:

HDI, Cluster Analysis, K-Means, Manhattan Distance

Abstract

This research aims to see the distribution of HDI in Indonesia as seen from its grouping based on its constituent components. The panel data regression model is formed from the results of cluster analysis using the K-means method using the Manhattan distance. The data used for cluster analysis is the panel data of the HDI components by province in 2010-2019. The results of the cluster analysis form 5 optimum groups, with the characteristics of group 1, HDI is relatively moderate, group 2 is also relatively moderate but not better than group 1, group 3 is relatively high, group 4 is relatively low, and group 5 is relatively very high.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2021-02-28

Issue

Volume 8, Issue 1, January-February-2021

Section

Research Articles

License

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Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Azlam Nas, Sri Mulatsih, Muhammad Findi "Regional Clustering Based On HDI Components In Indonesia" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 8, Issue 1, pp.21-25, January-February-2021. Available at doi : https://doi.org/10.32628/IJSRSET21813