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