Klasterisasi Pendapatan Nasional dan Pola Konsumsi Negara-Negara G20 Tahun 2023 Menggunakan Metode K-Means
DOI:
https://doi.org/10.32493/sm.v8i1.55980Keywords:
Cluster Analysis, Economic Growth, G20 Countries, Income Level, K-MeansAbstract
The G20 countries are often treated as a relatively homogeneous group in macroeconomic analysis, despite
substantial differences in income levels, economic growth, and consumption patterns among member countries.
This study aims to classify G20 countries based on national income, economic growth, and consumption
indicators in order to identify structural differences in their economic characteristics. The analysis employs
the K-Means clustering method using standardized data to ensure comparability across variables with different
measurement scales. Prior to clustering, data standardization is applied using the Z-score method. The optimal
number of clusters is determined using a cluster validity measure, and the clustering process is performed
using Euclidean distance. The results indicate that the optimal clustering structure is achieved with three
clusters. The K-Means algorithm successfully groups G20 countries into three distinct clusters with clearly
differentiated economic profiles. The centroid analysis reveals that each cluster exhibits unique characteristics
in terms of income level, growth dynamics, and consumption patterns, allowing for objective and data-driven
cluster categorization. The findings also show that higher income levels are not always associated with higher
consumption patterns, and that developing economies tend to form a separate cluster characterized by
relatively higher economic growth. The evaluation of cluster quality indicates good cohesion within clusters
and clear separation between clusters, suggesting that the clustering results are valid and reliable. Overall,
this study demonstrates that cluster analysis provides an effective framework for capturing the heterogeneity
of economic structures among G20 countries. The findings contribute to a more nuanced understanding of
global economic diversity and may serve as a basis for comparative economic analysis and policy oriented
discussions.
References
Adams, J. J., & Rojas, E. (2024). Household Consumption and Dispersed Information. Journal of Monetary Economics, 147, 103592. https://doi.org/10.1016/j.jmoneco.2024.103592
Ariani, A. R., & Doni, A. H. (2025). Pengaruh pengeluaran konsumsi rumah tangga terhadap pertumbuhan ekonomi Provinsi Sumatera Barat tahun 1988–2023. Jurnal Ekonomi Dan Bisnis, 3(3021–8365), 635–706.
Asrida, Haryani, Muttaqim, H., & Ernita. (2023). PENGARUH INFLASI DAN PENDAPATAN PERKAPITA TERHADAP KONSUMSI RUMAH TANGGA DI INDONESIA Asrida, Haryani, Hakim Muttaqim dan Ernita. Jurnal Ilmiah Sains, Teknologi, Ekonomi, Sosial Dan Budaya, 7(4).
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis. Book.
Hennig, C. (2007). Cluster-wise assessment of cluster stability. Computational Statistics & Data Analysis, 52, 258–271. https://doi.org/10.1016/j.csda.2006.11.025
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2023). An Introduction to Statistical Learning with Applications in R Second Edition.
Johnson, R. A., & Wichern, D. W. (2007). Applied_Multivariate_Statistical_Analysi. https://search.worldcat.org/en/title/70867129
Kodinariya, T. M., & Makwana, P. R. (2013). Review on determining number of Cluster in K-Means Clustering. International Journal of Advance Research in Computer Science and Management Studies, 1(6). www.ijarcsms.com
Laborda, J., & Suárez, C. (2024). Heterogeneity in household consumption behavior: The role of inequality and financial instability. Journal of Evolutionary Economics, 34(1), 63–88. https://doi.org/10.1007/s00191-024-00853-x
Solechah, W. M., & Sugito, S. (2023). Pembangunan Ekonomi Berkelanjutan sebagai Kepentingan Nasional Indonesia dalam Presidensi G-20. Dialektika : Jurnal Ekonomi Dan Ilmu Sosial, 8(1), 12–23. https://doi.org/10.36636/dialektika.v8i1.1487
Wahlian, R., Munjayanah, A., & Prasetyo, P. E. (2024). Determinants of Household Consumption in Indonesia 2018-2020. Efficient: Indonesian Journal of Development Economics, 7(1), 82. https://doi.org/10.15294/r8hpwj45
Yudanto, D., Rochaida, E., Ekonomi dan Bisnis, F., & Mulawarman, U. (n.d.). Pengaruh pendapatan perkapita dan inflasi serta suku bunga terhadap konsumsi rumah tangga makanan dan non makanan serta pengaruhnya terhadap kesejahteraan masyarakat. J A, 17(2), 2020–2287. http://journal.feb.unmul.ac.id/index.php/KINERJA
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