Analysis of Inflation Rates During and After the COVID-19 Pandemic Using the K-Means Clustering Method and Kruskal-Wallis Test

Riska Nuril Fadhila, Nurissaidah Ulinnuha, Moh Hafiyusholeh — Fri, 21 Nov 2025 00:00:00 +0700

Inflation occurs when excessive demand results in an overall increase in the prices of goods and services. During the COVID-19 pandemic, the inflation rate in Indonesia leveled off due to the weakening economy. However, in 2022, there was a spike in post-COVID-19 inflation due to increased public demand as pandemic conditions improved. Stable inflation is a requirement for sustainable economic growth and improving people's welfare. In handling inflation problems in various regions, variables and unique circumstances in each region are very important. This research aims to determine whether significant differences exist in the clustering of inflation rates in Indonesia during and after the COVID-19 pandemic. The research results using the Kruskal-Wallis test and the K-Means method obtained that the clustering of inflation rates with k=2 provides good results, as indicated by the Silhouette Coefficient value of 0.66. In addition, there is a significant difference between the current (2020-2021) and post (2022-2023) years of COVID-19 as evidenced by the Kruskal-Wallis test with a p-value < 0.05.

ANALISIS HIERARCHICAL CLUSTERING (SINGLE LINKAGE) DAN K-MEDOIDS PADA DATA PENGHASILAN DAN DEMOGRAFI AREA KOMUNITAS CHICAGO

Fri, 21 Nov 2025 00:00:00 +0700

Penelitian ini menganalisis metode Hierarchical Clustering Single Linkage dan K-Medoids dalam mengelompokkan data
pendapatan dan demografi di Chicago. Dengan menggunakan data sekunder dari situs Kaggle, penelitian
ini mengelompokkan 77 komunitas area berdasarkan kesamaan karakteristik sosial dan ekonomi. Hasil analisis dengan
metode Hierarchical Clustering Single Linkage menunjukkan bahwa terdapat satu komunitas area yang terpisah dalam
klaster kedua, sementara sisanya tergabung dalam satu klaster utama. Sebaliknya, metode K-Medoids menghasilkan dua
klaster yang lebih seimbang dalam distribusi datanya. Berdasarkan visualisasi clustering, metode K-Medoids dianggap
lebih baik karena mampu membagi data secara lebih seimbang. Namun, jika ditinjau dari nilai Silhouette Score dan Dunn
Index, metode Hierarchical Clustering Single Linkage lebih unggul karena memiliki nilai yang lebih tinggi, menunjukkan fragmentasi
klaster yang lebih jelas. Dengan demikian, pemilihan metode terbaik bergantung pada tujuan analisis, di mana
K-Medoids lebih sesuai untuk interpretasi distribusi data yang lebih merata, sedangkan Hierarchical Clustering Single
Linkage lebih optimal dalam kriteria klaster yang jelas.

This study analyzes the Hierarchical Clustering Single Linkage and K-Medoids methods in clustering income and demographic data of communities in Chicago. Using secondary data from the Kaggle website, this study clusters 77 community areas based on similarities in social and economic characteristics. The analysis using the Hierarchical Clustering Single Linkage method reveals that one community area is isolated in the second cluster, while the rest are grouped into a single main cluster. In contrast, the K-Medoids method produces two clusters with a more balanced distribution. Based on clustering visualization, the K-Medoids method is considered superior as it provides a more evenly distributed classification. However, when evaluated using the Silhouette Score and Dunn Index, the Hierarchical Clustering Single Linkage method outperforms K-Medoids due to its higher values, indicating clearer cluster separation. Thus, the choice of the best method depends on the analytical objective, where K-Medoids is more suitable for interpreting a more balanced data distribution, while Hierarchical Clustering Single Linkage is optimal for achieving distinct cluster separation.

Jurnal Fourier

Analysis of Inflation Rates During and After the COVID-19 Pandemic Using the K-Means Clustering Method and Kruskal-Wallis Test

ANALISIS HIERARCHICAL CLUSTERING (SINGLE LINKAGE) DAN K-MEDOIDS PADA DATA PENGHASILAN DAN DEMOGRAFI AREA KOMUNITAS CHICAGO