Abstract
This study focuses on the role of financing the ultra microprogram (UMi) to support government programs in poverty alleviation. There are two analyzes used: first descriptive analysis, which compares the number of micro-enterprises with the number of poor people in Central Java. Second, statistical analysis of Pearson correlation measures the correlation between the number of micro-entrepreneurs, the amount of ultra-micro credit financing disbursement, the number of poor people, and indicators related to poverty. The results of the descriptive analysis show that before the covid-19 pandemic, the average percentage of micro-enterprises and the number of poor people was 4.09 percent. In comparison, during the covid-19 pandemic, the average was 5.40 percent. Pearson correlation statistical analysis shows that the number of customers and the distribution of ultra-micro credit strongly correlate with the number of poor people. The number of poor people has a strong correlation with life expectancy and an average length of schooling. It has a reasonably strong correlation with other indicators related to poverty both before the 2019 COVID-19 pandemic and during the 2020 COVID-19 pandemic.
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More From: Journal of Business and Information Systems (e-ISSN: 2685-2543)
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