Yeky Abil Nizar, M. Susilawati, I. G. A. M. Srinadi
{"title":"当采用地理加权回归（GWR）方法时，银行在CAPTAINS中的活动和作为时间供应成本提出了一个模型","authors":"Yeky Abil Nizar, M. Susilawati, I. G. A. M. Srinadi","doi":"10.24843/mtk.2023.v12.i03.p423","DOIUrl":null,"url":null,"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%.","PeriodicalId":11600,"journal":{"name":"E-Jurnal Matematika","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A PEMODELAN JUMLAH KEJADIAN BANJIR DI KABUPATEN DAN KOTA PROVINSI JAWA TIMUR DENGAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR)\",\"authors\":\"Yeky Abil Nizar, M. Susilawati, I. G. A. M. Srinadi\",\"doi\":\"10.24843/mtk.2023.v12.i03.p423\",\"DOIUrl\":null,\"url\":null,\"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%.\",\"PeriodicalId\":11600,\"journal\":{\"name\":\"E-Jurnal Matematika\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"E-Jurnal Matematika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24843/mtk.2023.v12.i03.p423\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"E-Jurnal Matematika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24843/mtk.2023.v12.i03.p423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
东爪哇省是一个经历过多次洪水灾害的省份。洪水是一种自然灾害事件，通常受一个地区无法容纳高降雨量的影响，每个地区的降雨量不同。本研究旨在通过可预测的变量，包括人口密度、雨天数量、降雨量、湿度、人口增长率和开发用地，确定可能在东爪哇省引发洪水的模型和因素。能够在这些条件下对案例进行建模的回归方法是地理加权回归（GWR）。研究数据来源于中央统计局、POWER data Access Viewer和环境与林业部。最佳模型可以用决定系数来表示，其中GWR获得了更大的决定系数，即65.37%，而线性回归中的决定系数等于31.19%，SAR的决定系数为36.26%。
A PEMODELAN JUMLAH KEJADIAN BANJIR DI KABUPATEN DAN KOTA PROVINSI JAWA TIMUR DENGAN METODE GEOGRAPHICALLY WEIGHTED REGRESSION (GWR)
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%.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
