APLIKASI REGRESI SPLINE TRUNCATED PADA DAMPAK KEBAKARAN HUTAN TERHADAP PENDERITA ISPA DI PROVINSI RIAU TAHUN 2015-2020
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Date
2022-12
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Elfitra
Abstract
Forest fires are a crucial problem in Riau Province because they cause haze pollution
that affects public activities and health. In 2019, based on data from the Health Office,
victims of ARI disease have reached 281,626 people. Factors that are suspected to affect
the number of people with ARI disease are nitrogen dioxide (𝑁02), sulfur dioxide (𝑆02),
the number of hotspots, and the area of burnt areas. In this study, skunder data from
2015-2020 was used in 12 districts of Riau Province, by looking at the scatterplot of
each variable that is suspected to be influential and does not have a certain pattern so
that using the truncated spline regression method, the selection of the optimum knot
point of the smallest generalized cross validation value is able to provide the best
truncated spline regression model, the results of the method obtained can explain the
forest fire against the large number of ARI sufferers. There are 2 variables that
significantly affect the number of people with ARI, namely (𝑁02) and hotspots.
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Keywords
Forest fires, scatterplots, truncated spline regression, the selection of the optimum knot point, and generalized cross validation
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