A PEMODELAN JUMLAH KEJADIAN BANJIR DI KABUPATEN DAN KOTA PROVINSI JAWA TIMUR DENGAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR)
on
Authors:
YEKY ABIL NIZAR, MADE SUSILAWATI, I GUSTI AYU MADE SRINADI
Abstract:
“East Java Province is a province that experiences many flood disasters. Floods are natural disaster events that are generally affected by the inability of an area to accommodate high rainfall, where rainfall is different in each region. This study aims to determine models and factors that can significantly cause floods in East Java Province with predictable variables including population density, number of rainy days, rainfall, humidity, population growth rate and development land use. The regression method that is able to model cases with these conditions is Geographically Weighted Regression (GWR). Source of research data were obtained from the Central Statistic Agency, POWER Data Access Viewer and Ministry of Environment and Forestry. The best model can be shown by the coefficient of determination, where the GWR obtains a greater coefficient of determination, namely 65.37% compared to the coefficient of determination in linear regression, which is equal to 31.19%, and the coefficient of determination of SAR is 36.26%.”
Keywords
Keyword Not Available
Downloads:
Download data is not yet available.
References
References Not Available
PDF:
https://jurnal.harianregional.com/mtk/full-104669
Published
2023-08-23
How To Cite
NIZAR, YEKY ABIL; SUSILAWATI, MADE; SRINADI, I GUSTI AYU MADE. A PEMODELAN JUMLAH KEJADIAN BANJIR DI KABUPATEN DAN KOTA PROVINSI JAWA TIMUR DENGAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR).E-Jurnal Matematika, [S.l.], v. 12, n. 3, p. 227-233, aug. 2023. ISSN 2303-1751. Available at: https://jurnal.harianregional.com/mtk/id-104669. Date accessed: 08 Jul. 2024. doi:https://doi.org/10.24843/MTK.2023.v12.i03.p423.
Citation Format
ABNT, APA, BibTeX, CBE, EndNote - EndNote format (Macintosh & Windows), MLA, ProCite - RIS format (Macintosh & Windows), RefWorks, Reference Manager - RIS format (Windows only), Turabian
Issue
Vol 12 No 3 (2023)
Section
Articles
Copyright
This work is licensed under a Creative Commons Attribution 4.0 International License
Discussion and feedback