Negative Binomial Panel Regression Modeling on Amount of Crimes In Lampung Province - Suratmin, Idam Abdurrohim Hasani; Agustina, Dian; Agwil, Winalia (EKSAKTA: Journal of Sciences and Data Analysis, 2024)
Crime in Lampung province is among the 10 highest in Indonesia in 2021. This study aims to obtain a model of the number of crimes and factors influencing it using negative binomial panel regression. The data used is in the form of panel data from the Lampung Province BPS website and publications for 2017-2021. The condition of data on the number of crimes as discrete and overdispersed data makes the negative binomial panel regression method more suitable than Poisson panel regression. Overdispersion is a state where the variance of the data is greater than the mean value of the data. Overdispersion causes the standard error (SE) of the estimated value to decrease, so that variables that should not be significant become significant. The factors thought to be the cause of crime are percentage of poverty (X1), population density (X2), expenditure per capita (X3), unemployment rate (X4), regional gross domestic income (X5), and the average duration of schooling (X6). The results of the analysis obtained for the selected panel data model are the negative binomial random effects (REBN), the influencing factors being X1, X3, X4 and X5. The districts/cities with the largest individual random effects were in the Way Kanan district and the smallest were in Metro City.