Jurnal Tekinkom (Teknik Informasi dan Komputer)
Vol 5 No 2 (2022)

DATA MINING UNTUK KLASIFIKASI STATUS PANDEMI COVID 19

Pastima Simanjuntak (Universitas Putera Batam)
Cosmas Eko Suharyanto (Universitas Putera Batam)
Sunarsan Sitohang (Universitas Putera Batam)
Koko Handoko (Universitas Putera Batam)



Article Info

Publish Date
31 Dec 2022

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.

Copyrights © 2022






Journal Info

Abbrev

Tekinkom

Publisher

Subject

Computer Science & IT

Description

Jurnal TEKINKOM merupakan jurnal yang dimaksudkan sebagai media terbitan kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai isu Ilmu - ilmu komputer dan sistem informasi, seperti : Pemrograman Jaringan, Jaringan Komputer, Teknik Komputer, Ilmu Komputer/Informatika, Sistem ...