Geographically Weighted Panel Regression Modelling of Dengue Hemorrhagic Fever Data Using Exponential  Kernel Function

Risti Raihani; Sifriyani Sifriyani; Surya Prangga

doi:10.31764/jtam.v7i4.16235

Geographically Weighted Panel Regression Modelling of Dengue Hemorrhagic Fever Data Using Exponential Kernel Function

Risti Raihani, Sifriyani Sifriyani, Surya Prangga

Abstract

Geographically Weighted Panel Regression (GWPR) model is a panel regression
model applied to spatial data. This research takes the Fixed Effect Model (FEM)
panel regression as the global model and GWPR as the local model for dengue
hemorrhagic fever (DHF) in East Kalimantan Province data over the years 2018-
2020. DHF is a disease that has the potential to become an extraordinary event
which is accompanied by death. In comparison to Indonesia, East Kalimantan
Province's DHF Incident Rate (IR) was high in 2020. East Kalimantan's IR is 60.6
per 100,000 population, compared to Indonesia's IR of 40.0 per 100,000
population. This research aims to obtain the GWPR model, as well as to acquire
factors that affect DHF in East Kalimantan Province over the years 2018-2020
based GWPR model. The parameter of the GWPR model was estimated on each
observation location using the Weighted Least Square (WLS) method, which is an
Ordinary Least Square (OLS) with the addition of spatial weighting. The spatial
weighting on the GWPR model was determined by the best weighting function
between fixed exponential and adaptive exponential. The optimum weighting
function with a minimum cross-validation (CV) value of 1.7317×106 is adaptive
exponential. Based on GWPR parameter testing, factors that affect DHF are local
and diverse in each 10 regencies/municipalities in East Kalimantan Province.
These factors are population density, number of health facilities, percentage of
proper sanitation use in the household, percentage of household with qualified
drinking water sources, and percentage of health services. The coefficient of
determination of the GWPR model obtains a higher value than the FEM, which is
95.33%. Based on the measurement of goodness using the coefficient of
determination value, it can be concluded that GWPR is the best method to model
the DHF data rather than the FEM.

Keywords

Adaptive Exponential; Panel Regression; Fixed Effect Model; Geographically Weighted Panel Regression; Dengue Hemorrhagic Fever.

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DOI: https://doi.org/10.31764/jtam.v7i4.16235