Modeling the Number of High School Dropouts Using GWGPR
Abstract
In 2022, the high school dropout rate is the highest compared to other levels of education in Indonesia.
Seeing the urgency of the 12-year Compulsory Education program, completing education up to the high
school level is an important thing that needs to be considered. Thus, it is necessary to know the factors
that influence the dropout rate in the hope that this problem can be reduced. This study aims to model
the high school dropout rate using geographically weighted generalized poisson regression (GWGPR)
based on the factors that influence it. GWGPR is used if the response variable is overdispersed and
depends on the location observed. The results of this study indicate that each province has a different regression model. The GWGPR model with the adaptive tricube kernel weighting function is the
best model because it has the smallest AIC value compared to other weighting functions. In Central
Sulawesi Province, the GWGPR model with the adaptive tricube kernel weighting function formed is
µˆ26 = exp (8, 1267 − 0, 1267X4 + 0, 0344X5 + 0, 0957X6 + 0, 1173X7). With the significant variables are the average length of schooling, the percentage of the population aged 7-17 years who receive
PIP, the open unemployment rate, and the percentage of children who do not live with parents.
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