DATA MINING UNTUK KLASIFIKASI STATUS PANDEMI COVID 19

Pastima Simanjuntak, Cosmas Eko Suharyanto, Sunarsan Sitohang, Koko Handoko
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引用次数: 2

Abstract

We all know that since the number of Covid-19 cases has increased in Indonesia, many problems have arisen in society. Covid-19 has crippled the socio-economic conditions of all Indonesian people. As a result of the Covid-19 problem, the Indonesian government must establish policies such as issuing rules for social distancing, and also calling for Work From Home for those who work as employees, imposing restrictions on each region, building hospitals to handle Covid-19, and others. With the existence of government policy decisions will have an impact on all people, both the community. Socio-economic problems arise and have a direct impact on society. The purpose of this study is to prediction the covid 19 pandemic. This study applies data mining techniques with the naïve Bayes algorithm with software implementation using Tanagra software. The results of this study can be used to see the clustering pattern of the Covid 19 pandemic, and it can be seen from the results of the probabilities of the Covid data so far for the spread of Covid 19 which has 90.7% correct predictions and 9.3% wrong predictions.
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大家都知道,印尼新冠肺炎确诊病例增加以来,社会上出现了不少问题。新冠肺炎疫情严重影响了全体印尼人民的社会经济状况。由于新冠肺炎问题,印度尼西亚政府必须制定政策,例如发布社交距离规则,要求员工在家工作,对每个地区实施限制,建立医院以应对新冠肺炎等。有了政府的存在,政策决定就会对所有人、社会都产生影响。社会经济问题出现并对社会产生直接影响。本研究的目的是预测covid - 19大流行。本研究将数据挖掘技术应用于naïve贝叶斯算法,并使用Tanagra软件实现。本研究的结果可以看出Covid - 19大流行的聚类模式,从目前为止Covid数据的概率结果可以看出,Covid - 19的传播预测有90.7%的正确预测和9.3%的错误预测。
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