The Application of Logistic Regression to Measure the Impact of Covid-19 Pandemic on Household Credit Financing - Nurtiyasari, Devi Nurtiyasari; Syahputra, Angga; Hilmi, Rashif (Quadratic: Journal of Innovation and Technology in Mathematics and Mathematics Education, 2021)
The spread of the Covid-19 outbreak has a direct impact on the economic sector. The impact of Covid-19 on the economic sector can be seen from Non-Performing Loans (NPL). Credit financing affects the Financial System Stability. Furthermore, households are the sector most affected by Covid-19, because household income is obtained from other sectors that are also affected by the spread of Covid-19. This impact can be seen in terms of income, savings/assets, and consumption. This study aims to analyze the impact of Covid-19 as measured by the variables of income, savings/assets, and consumption on household credit financing using the Logistic Regression Model. The modelling results show that the consumption and savings variables do not have a significant effect on household credit financing, while the income variables have a significant effect and are able to predict 15.5% of the variability of household credit financing. Furthermore, based on the odds ratio value of the model, information is obtained that the effect of decreased household income during the Covid-19 pandemic affected one time on the value of the odds ratio for household credit financing. Overall, the model was able to predict the data correctly by 81.4%.