Proceedings of the 12th International Conference on Green Technology (ICGT 2022)

# Agglomerative Hierarchical Clustering Analysis Based on Partially-Ordered Hasse Graph of Poverty Indicators in East Java

Authors
Ina Maya Sabara1, *, Fachrur Rozi2, Mohammad Nafie Jauhari2
1Magister Students of Mathematics Education Study Program, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Malang, Indonesia
2Mathematics Study Program, Faculty of Science and Technology, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Malang, Indonesia
*Corresponding author. Email: 220108210004@student.uin-malang.ac.id
Corresponding Author
Ina Maya Sabara
Available Online 29 May 2023.
DOI
10.2991/978-94-6463-148-7_46How to use a DOI?
Keywords
Agglomerative Hierarchical Clustering; Hasse Graph; Poverty; Cluster Validity Test; Partially-ordered
Abstract

Poverty is a central issue in many countries, so one of the main goals of a country is to eradicate poverty. One of the efforts is to identify indicators that affect poverty using cluster analysis. In this research, we discuss cluster analysis using the agglomerative hierarchical clustering method based on the partially-ordered Hasse graph. Meanwhile, one form of facilitating cluster analysis is the Hasse graph. Therefore, this study was conducted to find out which areas have close or similar poverty indicators based on the partially-ordered Hasse graph and reduce the incidence of poverty in East Java. Before conducting cluster analysis, a multicollinearity test was carried out between poverty indicators, then the proximity between objects was determined using the Euclidean distance. Afterward, cluster analysis was performed using agglomerative methods (single linkage and complete linkage) to obtain the best cluster solution. The single linkage method provides the best solution consisting of five clusters. The results of the partially-ordered Hasse graph show that the fifth cluster becomes the top layer based on the Gini indicator. The fourth cluster becomes the top layer based on the depth index indicator. Last, the first cluster becomes the top layer based on the open unemployment rate indicator and life expectancy.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Volume Title
Proceedings of the 12th International Conference on Green Technology (ICGT 2022)
Series
Advances in Engineering Research
Publication Date
29 May 2023
ISBN
10.2991/978-94-6463-148-7_46
ISSN
2352-5401
DOI
10.2991/978-94-6463-148-7_46How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

### Cite this article

TY  - CONF
AU  - Ina Maya Sabara
AU  - Fachrur Rozi
AU  - Mohammad Nafie Jauhari
PY  - 2023
DA  - 2023/05/29
TI  - Agglomerative Hierarchical Clustering Analysis Based on Partially-Ordered Hasse Graph of Poverty Indicators in East Java
BT  - Proceedings of the 12th International Conference on Green Technology (ICGT 2022)
PB  - Atlantis Press
SP  - 460
EP  - 469
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-148-7_46
DO  - 10.2991/978-94-6463-148-7_46
ID  - Sabara2023
ER  -