Analysis and Clustering of Poverty Levels by Education in Cimahi City Using the BIRCH Method (Balanced Iterative Reducing and Clustering using Hierarchies)

Poverty is an important issue for the local government of Cimahi City, mainly caused by the low level of education of the community and unequal access to quality educational facilities. Given the role of education in influencing the economic condition of the community, this study aims to examine the causes of poverty. Demographic factors such as income, social economic status, and educational attainment are examined in this study using data from the Education Department and Social Department of Cimahi City from 2019 to 2024. There are three poverty levels categorized based on the BIRCH method high, medium, and low. Cigugur Tengah and Leuwigajah area have a majority of residents with a high school education or less and a high poverty rate, while Baros and Padasuka Urban Village have a majority of residents with a D3-D4 education and a low poverty rate. However, the clustering results of the BIRCH method only yielded an accuracy of 43%, which shows that this model is not optimal in clustering poverty levels. According to these results, a region's chance of overcoming poverty increases with the average educational level of its population. The results of this study indicate that education plays an important role in helping people out of poverty. Therefore, the expansion of educational opportunities and an increase in public awareness of the value of education are key solutions.

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Publication Details

Journal
Brilliance Research of Artificial Intelligence
Published
2025-03-24
DOI
https://doi.org/10.47709/brilliance.v5i1.5631
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Analysis and Clustering of Poverty Levels by Education in Cimahi City Using the BIRCH Method (Balanced Iterative Reducing and Clustering using Hierarchies)

Ari Wibowo, Fadhilla Artamevia Putri Ristiawan
Brilliance Research of Artificial Intelligence
Data Mining and Machine Learning Applications
article

Analysis and Clustering of Poverty Levels by Education in Cimahi City Using the BIRCH Method (Balanced Iterative Reducing and Clustering using Hierarchies)

Ari Wibowo, Fadhilla Artamevia Putri Ristiawan
article en

Abstract

Poverty is an important issue for the local government of Cimahi City, mainly caused by the low level of education of the community and unequal access to quality educational facilities. Given the role of education in influencing the economic condition of the community, this study aims to examine the causes of poverty. Demographic factors such as income, social economic status, and educational attainment are examined in this study using data from the Education Department and Social Department of Cimahi City from 2019 to 2024. There are three poverty levels categorized based on the BIRCH method high, medium, and low. Cigugur Tengah and Leuwigajah area have a majority of residents with a high school education or less and a high poverty rate, while Baros and Padasuka Urban Village have a majority of residents with a D3-D4 education and a low poverty rate. However, the clustering results of the BIRCH method only yielded an accuracy of 43%, which shows that this model is not optimal in clustering poverty levels. According to these results, a region's chance of overcoming poverty increases with the average educational level of its population. The results of this study indicate that education plays an important role in helping people out of poverty. Therefore, the expansion of educational opportunities and an increase in public awareness of the value of education are key solutions.

Brilliance Research of Artificial IntelligenceVol. 5(1)
Universitas Widyatama (ID)
Openalex Percentile: Top 74%
Data Mining and Machine Learning Applications
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