PEMODELAN REGRESI SPLINE PADA FAKTOR YANG MEMPENGARUHI TINGKAT KEMISKINAN DI INDONESIA
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Date
2023-10
Authors
Zilmuarif, Firsan
Journal Title
Journal ISSN
Volume Title
Publisher
Elfitra
Abstract
Indonesia is one of the countries that is still struggling to overcome problems related to
poverty. Based on official statistical news, in March 2020 the percentage of the poor
population was recorded at 9.78%, which has increased periodically until September 2020
at 10.19% and in March 2021 at 10.14%, which is around 27.54 million. Although at the
end of March 2022 the percentage of poor people in Indonesia decreased by 0.17% against
September 2021, which is a decrease of around 0.34 million people. This study aims to
model poverty in Indonesia with factors that are thought to affect it using spline
nonparametric regression methods. This study obtained the best model, which is spline
regression using a combination knot point (2,3,3,1,1) with a minimum GCV of 21.315.
Of the five independent variables that have been tested, all variables have a significant
effect on the poverty rate in Indonesia in 2021, namely the IPM, PDRB, TPT, and RLS
variables.
Description
Keywords
Poverty, nonparametric regression, spline regression
Citation
Perpustakaan