Comparative Analysis of Hierarchical Cluster Methods in Inflationary Cities in Indonesia Based on Sectoral Inflation Patterns
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H. A. Khoirunissa, A. R. Wijaya, B. Isnaini, and K. Ferawati, “Analisis Faktor-Faktor Penyebab Inflasi di Indonesia Menggunakan Regresi Ridge, LASSO, dan Elastic-Net,” Indones. J. Appl. Stat., vol. 7, no. 2, p. 121, Jan. 2025, doi: 10.13057/ijas.v7i2.96921.
F. Ferrante, S. Graves, and M. Iacoviello, “The inflationary effects of sectoral reallocation,” J. Monet. Econ., vol. 140, pp. S64–S81, Nov. 2023, doi: 10.1016/j.jmoneco.2023.03.003.
A. Jaeger and D. Banks, “Cluster analysis: A modern statistical review,” WIREs Comput. Stat., vol. 15, no. 3, May 2023, doi: 10.1002/wics.1597.
I. Nur and L. Fitriana, “Pengelompokan Provinsi di Indonesia Berdasarkan Indikator Keluarga Sehat Menggunakan Metode Klaster Hirarki dan Non Hirarki,” J. Paradig. J. Multidisipliner Mhs. Pascasarj. Indones., vol. 2, no. 1, pp. 27–36, 2021, [Online]. Available: https://journal.ugm.ac.id/paradigma/article/view/66072
A. R. Damayanti and A. W. Wijayanto, “Comparison of Hierarchical and Non-Hierarchical Methods in Clustering Cities in Java Island using the Human Development Index Indicators year 2018,” Eig. Math. J., pp. 8–17, Jun. 2021, doi: 10.29303/emj.v4i1.89.
A. Setiawan, B. Susanto, and T. Mahatma, “Inflation data clustering of some cities in Indonesia,” J. Phys. Conf. Ser., vol. 855, p. 012046, Jun. 2017, doi: 10.1088/1742-6596/855/1/012046.
A. Murjani, A. Pramila, and A. Rusyiana, “Analisis Klaster Kabupaten dan Kota di Kalimantan Selatan untuk Penentuan Kota Inflasi Acuan,” Ecoplan, vol. 5, no. 1, pp. 53–63, Apr. 2022, doi: 10.20527/ecoplan.v5i1.429.
S. Hidayatullah and A. Sofro, “Hierarchical Cluster Analysis Based on Waste Sources in Indonesia in 2022,” ComTech Comput. Math. Eng. Appl., vol. 15, no. 2, pp. 93–99, Nov. 2024, doi: 10.21512/comtech.v15i2.11088.
M. F. F. Mardianto et al., “Grouping of provinces in Indonesia based on community welfare level indicators using hierarchical cluster analysis,” 2023, p. 080015. doi: 10.1063/5.0181024.
S. Wulandari, “Clustering Indonesian Provinces on Prevalence of Stunting Toddlers Using Agglomerative Hierarchical Clustering,” Fakt. Exacta, vol. 16, no. 2, Jul. 2023, doi: 10.30998/faktorexacta.v16i2.17186.
L. P. Sari, A. Fanani, and A. H. Asyhar, “Analisis Perbandingan Pengelompokan Kota di Indonesia Berdasarkan Indikator Inflasi Tahun 2021 dengan Metode Ward dan K-Means,” J. Sains Mat. dan Stat., vol. 9, no. 2, p. 108, Aug. 2023, doi: 10.24014/jsms.v9i2.21100.
N. Etrisia, M. F. Alexandi, and A. Asmara, “KLASIFIKASI INFLASI 34 IBUKOTA PROVINSI DI INDONESIA SEBELUM DAN SAAT COVID-19 MELALUI PENGELOMPOKAN WILAYAH DENGAN K-MEANS CLUSTERING,” J. Ekon. Pembang., vol. 12, no. 2, pp. 120–133, Jul. 2023, doi: 10.23960/jep.v12i2.1597.
R. Gustriansyah, J. Alie, A. Sanmorino, R. Heriansyah, and M. N. Megat Mohamed Noor, “Machine Learning for Clustering Regencies-Cities Based on Inflation and Poverty Rates in Indonesia,” Indones. J. Inf. Syst., vol. 5, no. 1, pp. 64–73, Aug. 2022, doi: 10.24002/ijis.v5i1.5682.
J. Salomo and B. Siregar, “Cluster Analysis of Poverty Data in Cities/Districts in Indonesia Using K-Means Algorithm for the Years 2019–2022,” 2025, pp. 487–495. doi: 10.1007/978-981-97-3859-5_37.
S. Annas, B. Poerwanto, S. Sapriani, and M. F. S, “Implementation of K-Means Clustering on Poverty Indicators in Indonesia,” MATRIK J. Manajemen, Tek. Inform. dan Rekayasa Komput., vol. 21, no. 2, pp. 257–266, Mar. 2022, doi: 10.30812/matrik.v21i2.1289.
B. Simamora, Analisis Multivariat Pemasaran. Jakarta: Gramedia Pustaka Utama, 2005.
A. Smiti, “A critical overview of outlier detection methods,” Comput. Sci. Rev., vol. 38, p. 100306, Nov. 2020, doi: 10.1016/j.cosrev.2020.100306.
C. C. Aggarwal, “An Introduction to Outlier Analysis,” in Outlier Analysis, Cham: Springer International Publishing, 2017, pp. 1–34. doi: 10.1007/978-3-319-47578-3_1.
C. Essary, L. M. Fischer, and E. Irlbeck, “A Statistical Approach to Classification: A guide to hierarchical cluster analysis in agricultural communications research,” J. Appl. Commun., vol. 106, no. 3, Nov. 2022, doi: 10.4148/1051-0834.2431.
M. J. Bunkers, J. R. Miller, and A. T. DeGaetano, “Definition of Climate Regions in the Northern Plains Using an Objective Cluster Modification Technique,” J. Clim., vol. 9, no. 1, pp. 130–146, Jan. 1996, doi: 10.1175/1520-0442(1996)009<0130:DOCRIT>2.0.CO;2.
G. Brock, V. Pihur, S. Datta, and S. Datta, “clValid : An R Package for Cluster Validation,” J. Stat. Softw., vol. 25, no. 4, 2008, doi: 10.18637/jss.v025.i04.
X. Li, W. Liang, X. Zhang, S. Qing, and P.-C. Chang, “A cluster validity evaluation method for dynamically determining the near-optimal number of clusters,” Soft Comput., vol. 24, no. 12, pp. 9227–9241, Jun. 2020, doi: 10.1007/s00500-019-04449-7.
DOI: https://doi.org/10.37905/jjom.v8i1.35105
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