Analysis of Fuzzy C-Means Clustering Method on Grouping Provinces in Indonesia Based on Economic Growth in 2023

Economic growth is the process of increasing a country's capacity to provide goods and services to its population, which is an important indicator of the success of a region's development. The Fuzzy C-Means method was used to group provincial data in Indonesia based on economic growth in 2023 because of the ability of this technique to handle membership uncertainties that often occur. This research aims to understand the economic inequality that exists in various provinces, as well as provide useful information for the government in formulating more effective policies. The data used in this research is secondary data from the Central Statistics Agency, covering 34 provinces with important indicators in economic growth totaling 9 variables. The results of the analysis show that provinces in Indonesia can be grouped into two main clusters. The first cluster consists of provinces with relatively high economic growth, while the second cluster includes provinces with lower economic growth and higher levels of inequality. It is hoped that this research can provide a clear picture of the distribution of economic growth between provinces in Indonesia and assist the government in formulating appropriate strategies to improve economic prosperity evenly.

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Publication Details

Journal
International Journal of Scientific Research in Science Engineering and Technology
Published
2024-12-27
DOI
https://doi.org/10.32628/ijsrset2411466
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Analysis of Fuzzy C-Means Clustering Method on Grouping Provinces in Indonesia Based on Economic Growth in 2023

Muklas Rivai, Nadia Frasiska
International Journal of Scientific Research in Science Engineering and Technology
Data Mining and Machine Learning Applications
article

Analysis of Fuzzy C-Means Clustering Method on Grouping Provinces in Indonesia Based on Economic Growth in 2023

Muklas Rivai, Nadia Frasiska
article en

Abstract

Economic growth is the process of increasing a country's capacity to provide goods and services to its population, which is an important indicator of the success of a region's development. The Fuzzy C-Means method was used to group provincial data in Indonesia based on economic growth in 2023 because of the ability of this technique to handle membership uncertainties that often occur. This research aims to understand the economic inequality that exists in various provinces, as well as provide useful information for the government in formulating more effective policies. The data used in this research is secondary data from the Central Statistics Agency, covering 34 provinces with important indicators in economic growth totaling 9 variables. The results of the analysis show that provinces in Indonesia can be grouped into two main clusters. The first cluster consists of provinces with relatively high economic growth, while the second cluster includes provinces with lower economic growth and higher levels of inequality. It is hoped that this research can provide a clear picture of the distribution of economic growth between provinces in Indonesia and assist the government in formulating appropriate strategies to improve economic prosperity evenly.

International Journal of Scientific Research in Science Engineering and TechnologyVol. 11(6)
Institut Teknologi Medan (ID)
Decent work and economic growth
Openalex Percentile: Top 61%
Data Mining and Machine Learning Applications
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Analysis of Fuzzy C-Means Clustering Method on Grouping Provinces in Indonesia Based on Economic Growth in 2023 — Muklas Rivai, Nadia Frasiska · International Journal of Scientific Research in Science Engineering and Technology (2024) | TGRS Research Map | TGRS