IMPLEMENTASI AlGORITMA NAIVE BAYES UNTUK MEMPREDIKSI TINGKAT PENYEBARAN COVID

Rayuwati, Husna Gemasih, Irma Nizar
{"title":"IMPLEMENTASI AlGORITMA NAIVE BAYES UNTUK MEMPREDIKSI TINGKAT PENYEBARAN COVID","authors":"Rayuwati, Husna Gemasih, Irma Nizar","doi":"10.55606/jurritek.v1i1.127","DOIUrl":null,"url":null,"abstract":"The development of Information Technology (IT) is now very rapid and has been used in various aspects of life both in the field of government, banking, socio- cultural, industrial, education, and even health. One type of disease that gets attention for the application of IT is corona virus or better known as Covid 19 because the spread is quite widespread throughout the country, especially in the territory of Indonesia. Corona virus disease development in Indonesia is growing, based on WHO data as of today on August 30, 2020 positive cases have reached 172,053 people, cases died 7,343 people and recovered 124,185 people and the number of cases is increasing every day. Based on these conditions, Central Aceh is in a state of alert against the threat of corona virus. then a form of prevention  of the widespread spread of the virus can be done by breaking the chain of transmission by doing social distancing. In this study, a system will be designed to anticipate the Covid-19 pandemic by predicting the rate of spread of covid-19, especially in central Aceh districts using the Naive Bayes Classifier method. The accuracy level of this system is a positive case of 60%.","PeriodicalId":224124,"journal":{"name":"JURAL RISET RUMPUN ILMU TEKNIK","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JURAL RISET RUMPUN ILMU TEKNIK","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55606/jurritek.v1i1.127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The development of Information Technology (IT) is now very rapid and has been used in various aspects of life both in the field of government, banking, socio- cultural, industrial, education, and even health. One type of disease that gets attention for the application of IT is corona virus or better known as Covid 19 because the spread is quite widespread throughout the country, especially in the territory of Indonesia. Corona virus disease development in Indonesia is growing, based on WHO data as of today on August 30, 2020 positive cases have reached 172,053 people, cases died 7,343 people and recovered 124,185 people and the number of cases is increasing every day. Based on these conditions, Central Aceh is in a state of alert against the threat of corona virus. then a form of prevention  of the widespread spread of the virus can be done by breaking the chain of transmission by doing social distancing. In this study, a system will be designed to anticipate the Covid-19 pandemic by predicting the rate of spread of covid-19, especially in central Aceh districts using the Naive Bayes Classifier method. The accuracy level of this system is a positive case of 60%.
NAIVE BAYES算法的实施,以预测COVID的部署率
信息技术(IT)的发展现在非常迅速,已经在政府、银行、社会文化、工业、教育甚至卫生领域的生活的各个方面得到了应用。一种引起信息技术应用关注的疾病是冠状病毒,或者更广为人知的是Covid - 19,因为这种病毒在全国范围内传播非常广泛,尤其是在印度尼西亚境内。根据世卫组织截至今天(8月30日)的数据,印度尼西亚的冠状病毒疾病发展正在增长,2020年阳性病例已达到172053人,病例死亡7343人,康复124185人,病例数量每天都在增加。基于这些情况,中亚齐对冠状病毒的威胁处于警戒状态。然后,可以通过保持社会距离来打破传播链,从而预防病毒的广泛传播。在本研究中,将设计一个系统,通过使用朴素贝叶斯分类器方法预测Covid-19的传播速度,特别是在亚齐中部地区预测Covid-19大流行。该系统的准确率为60%以上。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信