基于K-means方法的印度尼西亚Covid-19聚类分析

Claudia Larasvaty, S. Khomsah, R. Sa
{"title":"基于K-means方法的印度尼西亚Covid-19聚类分析","authors":"Claudia Larasvaty, S. Khomsah, R. Sa","doi":"10.20895/dinda.v3i1.822","DOIUrl":null,"url":null,"abstract":"These days technology are rapidly increasing and developing in various fields, especially data storage. The information that has been stored in a database usually called a dataset. Covid-19 is a new type of respiratory disease that attacks the respiratory system with rapid transmission, followed by the increasing number of Covid-19 cases that continues to increase every day in all provinces in Indonesia. This study aims to cluster the spread of Covid-19 in every province in Indonesia by using the data that obtained from the website named kaggle with many data variables. The method used in this research is K-Means. From many variables in the data, for this study only 3 variables were taken, which are: Number of Recovery, Number of Deaths, and Number of total Cases in Covid-19 in Indonesia. These 3 variables then will be applied using the K-Means method and formed 3 provincial groups. By using the clustering method and the K-means algorithm, this research can be carried out to find the characteristics of the distribution in each province in Indonesia by looking at the best clusters.","PeriodicalId":419119,"journal":{"name":"Journal of Dinda : Data Science, Information Technology, and Data Analytics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cluster Analysis of Covid-19 in Indonesia Using K-means Method\",\"authors\":\"Claudia Larasvaty, S. Khomsah, R. Sa\",\"doi\":\"10.20895/dinda.v3i1.822\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"These days technology are rapidly increasing and developing in various fields, especially data storage. The information that has been stored in a database usually called a dataset. Covid-19 is a new type of respiratory disease that attacks the respiratory system with rapid transmission, followed by the increasing number of Covid-19 cases that continues to increase every day in all provinces in Indonesia. This study aims to cluster the spread of Covid-19 in every province in Indonesia by using the data that obtained from the website named kaggle with many data variables. The method used in this research is K-Means. From many variables in the data, for this study only 3 variables were taken, which are: Number of Recovery, Number of Deaths, and Number of total Cases in Covid-19 in Indonesia. These 3 variables then will be applied using the K-Means method and formed 3 provincial groups. By using the clustering method and the K-means algorithm, this research can be carried out to find the characteristics of the distribution in each province in Indonesia by looking at the best clusters.\",\"PeriodicalId\":419119,\"journal\":{\"name\":\"Journal of Dinda : Data Science, Information Technology, and Data Analytics\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Dinda : Data Science, Information Technology, and Data Analytics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20895/dinda.v3i1.822\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Dinda : Data Science, Information Technology, and Data Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20895/dinda.v3i1.822","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

近年来,技术在各个领域迅速发展,尤其是数据存储。存储在数据库中的信息通常称为数据集。Covid-19是一种攻击呼吸系统的新型呼吸系统疾病,传播迅速,随后印度尼西亚所有省份的Covid-19病例数量持续增加,每天都在增加。本研究旨在通过使用从名为kaggle的网站获得的具有许多数据变量的数据,将Covid-19在印度尼西亚每个省的传播聚集在一起。本研究使用的方法是K-Means。从数据中的许多变量中,本研究仅选取了3个变量,分别是:印度尼西亚Covid-19的康复人数、死亡人数和总病例数。然后将使用K-Means方法应用这3个变量并形成3个省组。本研究采用聚类方法和K-means算法,通过寻找最佳聚类,找出印尼各省份的分布特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cluster Analysis of Covid-19 in Indonesia Using K-means Method
These days technology are rapidly increasing and developing in various fields, especially data storage. The information that has been stored in a database usually called a dataset. Covid-19 is a new type of respiratory disease that attacks the respiratory system with rapid transmission, followed by the increasing number of Covid-19 cases that continues to increase every day in all provinces in Indonesia. This study aims to cluster the spread of Covid-19 in every province in Indonesia by using the data that obtained from the website named kaggle with many data variables. The method used in this research is K-Means. From many variables in the data, for this study only 3 variables were taken, which are: Number of Recovery, Number of Deaths, and Number of total Cases in Covid-19 in Indonesia. These 3 variables then will be applied using the K-Means method and formed 3 provincial groups. By using the clustering method and the K-means algorithm, this research can be carried out to find the characteristics of the distribution in each province in Indonesia by looking at the best clusters.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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