CLUSTER ANALYSIS FOR DISTRICT/CITY GROUPING BASED ON VARIABLES AFFECTING POVERTY IN ACEH PROVINCE USING AVERAGE LINKAGE METHOD

  • Mirda Olivia Mathematics Departments, Faculty of Engineering, Samudra University, Indonesia
  • Nurviana Nurviana Mathematics Departments, Faculty of Engineering, Samudra University, Indonesia
  • Fairus Fairus Mathematics Departments, Faculty of Engineering, Samudra University, Indonesia
DOI: https://doi.org/10.30598/barekengvol17iss4pp1865-1872
Keywords: Aceh, Average Linkage, Cluster Analysis, Poverty

Abstract

Poverty is an inability of a person/household to meet basic needs in everyday life. Aceh is one of the provinces in Indonesia which is still faced with the problem of poverty. In March 2021 the poor population in Aceh numbered 834.24 thousand people and in September 2021 the poor population in Aceh increased by 16 thousand people, a total of 850.26 thousand people. Therefore the authors are interested in classifying and looking at the characteristics of 23 districts/cities in Aceh Province based on 5 variables that affect poverty. This study uses data from SUSENAS processed from BPS Kota Langsa in 2021. The variables used are households with the type of floor of a residential building made of soil/bamboo (X1), households with a floor area of ​​a residential building < 10 m2 per capita (X2), households with residential walls made of bamboo/rumbia/wood (X3), households with a source of drinking water from unprotected wells/springs/rivers/rainwater (X5), and households whose head of household did not attend school/didn't finish primary school/only primary school (X8). This study uses the average linkage method, namely the distance between two clusters is measured by the average distance between objects in each cluster. Of the 23 regencies/cities, 3 clusters were formed, namely cluster 1 with the lowest poverty rate consisting of 17 regencies/cities. Cluster 2 with the highest poverty rate consists of 2 districts/cities. Cluster 3 with a moderate poverty level consists of 4 districts/cities. The characteristics of the clusters that are formed are in clusters 1, 2 and 3 the dominant poverty level is influenced by the variable X3, which means that there are still many households that have houses with inadequate wall types. In clusters 1 and 3 the poverty rate is not dominantly influenced by variable X1, which means that many households have houses with proper floor types. In cluster 2 the poverty rate is not dominantly influenced by variable X5, which means that many households consume drinking water from cleaner and more protected sources.

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Published
2023-12-18
How to Cite
[1]
M. Olivia, N. Nurviana, and F. Fairus, “CLUSTER ANALYSIS FOR DISTRICT/CITY GROUPING BASED ON VARIABLES AFFECTING POVERTY IN ACEH PROVINCE USING AVERAGE LINKAGE METHOD”, BAREKENG: J. Math. & App., vol. 17, no. 4, pp. 1865-1872, Dec. 2023.
Issue
Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Section
Articles

Copyright (c) 2023 Mirda Olivia, Nurviana Nurviana, Fairus Fairus

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