K-Means Clustering of Jambi Province Based on Economic Growth in 2023

Authors

  • Fathina Nafisa Putri Universitas Negeri Padang
  • Dina Fitria Universitas Negeri Padang
  • Admi Salma Universitas Negeri Padang

DOI:

https://doi.org/10.24036/ujsds/vol4-iss1/434

Keywords:

Economic Growth, Jambi Province, K-Means Clustering

Abstract

 

Economic growth describes a region’s economic condition. In Jambi Province, although recovery after the COVID-19 pandemic has been visible, gaps between districts and cities still exist due to income inequality, poverty, unemployment, and differences in human capital quality shown by the Human Development Index. This study aims to group districts/cities in Jambi Province based on economic growth and its determinants using the k-means clustering method. The analysis resulted in five clusters with distinct characteristics. Cluster 1, located in the central region, is characterized by relatively low economic growth and human capital, along with a high poverty rate. Cluster 2, covering areas in the western highlands and eastern region, shows strong human capital and a low poverty rate. Cluster 3, in the western part of the province, is marked by low poverty and unemployment rates. Cluster 4, situated in the northeastern coastal area, has the highest Gross Regional Domestic Product (GRDP) per capita and the lowest unemployment rate but struggles with a high poverty rate and weak human capital. Meanwhile, Cluster 5, representing the provincial capital area, demonstrates robust economic growth and strong human capital, although unemployment remains a key issue. These findings highlight the heterogeneity of regional conditions, suggesting that development policies must be tailored to each cluster to promote inclusive growth and equitable welfare.

Published

2026-02-28

How to Cite

Fathina Nafisa Putri, Dina Fitria, & Admi Salma. (2026). K-Means Clustering of Jambi Province Based on Economic Growth in 2023. UNP Journal of Statistics and Data Science, 4(1), 1–8. https://doi.org/10.24036/ujsds/vol4-iss1/434

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