Modeling of climate change vulnerability levels in Indonesia: Smoothing splines quantile regression
Abstract
Indonesia's forest area decreases every year and be the top four countries with the largest primary forest loss in the world. There is 99 percent of Indonesia's territory that is quite vulnerable to being very vulnerable to climate change. Considering the urgency of the climate change issue and the SDGs targets for handling impacts of climate change, this research will focus on the effect of deforestation on the climate change vulnerability levels in Indonesia. The smoothing spline quantile regression modeling was carried out because of the nonlinear relationship between deforestation and climate change vulnerability levels and data contains outlier. The result, deforestation has a significant positive effect on the distribution of villages based on vulnerability to climate change. The higher deforestation rate will increase climate change vulnerability levels. There are four provinces (Bangka Belitung, Riau Islands, South Kalimantan, and East Kalimantan) have a small number of villages with a very vulnerable level of climate change, and five provinces (Banten, East Nusa Tenggara, West Papua, Papua, and North Sumatera) have a large number of villages with a very vulnerable level of climate change. Forest protection strategies and avoiding permanent land conversion are management innovations that need to be implemented.
Copyright © 2022 Husnul Chotimah, Rinda Fitriani, Yudhie Andriyana. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article
H. Chotimah, R. Fitriani, Y. Andriyana, Modeling of climate change vulnerability levels in Indonesia: Smoothing splines quantile regression, J. Math. Comput. Sci. 12 (2022), 103. https://doi.org/10.28919/jmcs/7172
BibTeX
@article{Chotimah2022,
author = {Chotimah, Husnul and Fitriani, Rinda and Andriyana, Yudhie},
title = {Modeling of climate change vulnerability levels in Indonesia: Smoothing splines quantile regression},
journal = {J. Math. Comput. Sci.},
volume = {12},
year = {2022},
pages = {103},
doi = {10.28919/jmcs/7172}
}