Abstract
Post the COVID-19 pandemic has become a moment for economic recovery for countries around the world, including Indonesia. However, the intense competition in the market, aftershocks of the pandemic, extreme weather conditions, and rapid social, economic, and technological changes have made the global economic situation much more unstable. This has resulted in economic downturns in various countries. Nevertheless, the Indonesian economy has shown strong growth. The economic growth in Indonesia is supported by various factors in terms of demand, such as household consumption, and supply, such as the diversity of business fields. By using data from the Central Statistics Agency (BPS) regarding the factors supporting economic growth from the production side, this research aims to examine the determinant factors that affect the economic performance of East Java. Through Machine Learning analysis using principal component analysis and clustering analysis, certain characteristics were found among districts and cities in East Java. PCA was used to reduce the number of variables and resulted in several components that are consistent with general categorization. Urban areas consistently exhibit high human resource components, while another cluster shows high dependence on natural resources.
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