Classification Of Perceptions Of The Covid-19 Vaccine Using Multivariate Adaptive Regression Spline

Rizki Fitri Ananda, L. Harsyiah, Muhammad Rijal Alfian
{"title":"Classification Of Perceptions Of The Covid-19 Vaccine Using Multivariate Adaptive Regression Spline","authors":"Rizki Fitri Ananda, L. Harsyiah, Muhammad Rijal Alfian","doi":"10.30812/varian.v6i2.2639","DOIUrl":null,"url":null,"abstract":"Indonesia is one of the countries infected with the covid-19 virus. One of the government's efforts is the covid-19 vaccination. However, the covid-19 vaccination caused controversy for some people because many people refused to be vaccinated.  Public perception of the covid-19 vaccine can be categorized into two, namely positive and negative, based on survey from Indonesia ministry of health about acceptance of covid-19 vaccine state that this can be influenced by many factors. These factors are important to know as an effort to increase acceptance of covid-19. Multivariate Adaptive Regression Splines (MARS). The purpose of this study is to determine the classification model of public perception of the covid-19 vaccine and the factors that influence it. The method used in this study is Multivariate Adaptive Regression Splines (MARS). This method is appropriate classification method to be applied to categorical response variable data,  The outcomes demonstrate that the optimum mars model is produced by combining BF= 24, MI =3, MO= 1, and GCV=0.07340546. The resulting classification level is 91.5% with influencing factors yaitu gender (x_1), age (x_2), last education (x_4), willingness to vaccinate (x_6), education (x_8).  Based on the results obtained, the government can consider these factors for socialization","PeriodicalId":188119,"journal":{"name":"Jurnal Varian","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Varian","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30812/varian.v6i2.2639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Indonesia is one of the countries infected with the covid-19 virus. One of the government's efforts is the covid-19 vaccination. However, the covid-19 vaccination caused controversy for some people because many people refused to be vaccinated.  Public perception of the covid-19 vaccine can be categorized into two, namely positive and negative, based on survey from Indonesia ministry of health about acceptance of covid-19 vaccine state that this can be influenced by many factors. These factors are important to know as an effort to increase acceptance of covid-19. Multivariate Adaptive Regression Splines (MARS). The purpose of this study is to determine the classification model of public perception of the covid-19 vaccine and the factors that influence it. The method used in this study is Multivariate Adaptive Regression Splines (MARS). This method is appropriate classification method to be applied to categorical response variable data,  The outcomes demonstrate that the optimum mars model is produced by combining BF= 24, MI =3, MO= 1, and GCV=0.07340546. The resulting classification level is 91.5% with influencing factors yaitu gender (x_1), age (x_2), last education (x_4), willingness to vaccinate (x_6), education (x_8).  Based on the results obtained, the government can consider these factors for socialization
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于多变量自适应回归样条的Covid-19疫苗感知分类
印度尼西亚是感染covid-19病毒的国家之一。政府的努力之一是covid-19疫苗接种。然而,由于许多人拒绝接种疫苗,covid-19疫苗接种引起了一些人的争议。根据印度尼西亚卫生部关于covid-19疫苗接受度的调查,公众对covid-19疫苗的看法可分为积极和消极两种,这可能受到许多因素的影响。了解这些因素对于提高对covid-19的接受度很重要。多元自适应样条回归(MARS)。本研究的目的是确定公众对covid-19疫苗认知的分类模型及其影响因素。本研究使用的方法是多元自适应样条回归(MARS)。结果表明,当BF= 24, MI =3, MO= 1, GCV=0.07340546时,可以得到最优的火星模型。分类水平为91.5%,影响因素有性别(x_1)、年龄(x_2)、末受教育程度(x_4)、接种意愿(x_6)、受教育程度(x_8)。根据得到的结果,政府可以考虑这些因素进行社会化
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Application of Principal Component Regression in Analyzing Factors Affecting Human Development Index Impact of SST Anomalies on Coral Reefs Damage Based on Copula Analysis The NADI Mathematical Model on the Danger Level of the Bili-Bili Dam Regression Model of Land Area and Amount of Production to the Selling Price of Corn K-Means – Resilient Backpropagation Neural Network in Predicting Poverty Levels
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1