This study aims to determine the effect of banking financial performance on changes in MSME credit distribution. The data used is secondary data from Bank Indonesia through the 2017-2018 Commercial Bank Monthly Reports. Panel data regression analysis was carried out to determine the effect and model of bank performance variables and changes in MSME credit distribution variables. The results of this study indicate that the chosen model is FEM with SUR estimation and partially there is a significant influence between banking performance and changes in MSME lending. A 1% increase in bank profitabilitycould result in a 21% change in lending. However, insufficient evidence is not obtained to be able to show a significant effect between changes in lending and the ability of banks in existing capital to cover possible losses in credit or trading in securities and the capacity of funds that are ready to be lent.
This study was conducted to find patterns of relationships between 14 multidimensional poverty indicators in Indonesia from 2015-2019. To provide a more specific description of the relationship pattern, association rules with the apriori algorithm is used as the analysis method. The preprocessing stage to transform data was carried out using fuzzy functions and data reduction with Multiple Correspondence Analysis (MCA) to support the association analysis process. The results obtained are 15 relationship patterns or rules between items from the multidimensional poverty indicator with a support value of 60%-80% and 100% confidence. This means that the relationship pattern is significantly formed from objects with a strong relationship between the items and can represent poverty records in the last five years. The relationship pattern consists of four combinations of things. Suppose there is a high category decrease in the percentage of poor people indicator, a low category decrease in the open unemployment indicator, a high category increase in the percentage of households indicator according to the source of lighting from electricity, and a low category increase in the percentage indicator of households according to the broadest wall, not bamboo / other. In that case, there is a reduction in multidimensional poverty in Indonesia.
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