Negative Binomial Regression in Overcoming Overdispersion Poverty Data in Kalimantan

Poverty is one of the problems that Indonesia still faces. Kalimantan Island has large naturalresources, but experiences inequality in the distribution of wealth in the region. In this study, data onthe number of poor people is used as the dependent variable. The independent variables include thepercentage of households that have access to non-PLN electricity (X1), access to proper drinking water(X2), proper sanitation (X3), non-own toilet facilities (X4), HDI (X5), Open Unemployment Rate (X6),average wages of informal workers and main employment (X7), population density per km2 (X8),monthly per capita food and non-food expenditure (X9), percentage of the population who have healthcomplaints and do not treat because there is no cost (X10), and percentage of the population aged 15years and above who do not have a diploma (X11) in 2023. A Poisson regression analysis is employed.The model accounts for the significance of every independent variable. The model was found to haveoverdispersion, which was resolved through negative binomial regression. The findings of the studyrevealed that the average wage of informal workers and primary employment, population density perkm2, monthly per capita food and non-food expenditure, the percentage of the population who havehealth complaints but do not treat them because there is no cost, and the percentage of the populationaged 15 years and older who do not have a diploma all have a significant impact on the magnitude ofthe number of people living in poverty on the island of Kalimantan.