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

IMPLEMENTASI SISTEM PAKAR UNTUK DETEKSI DINI COVID VARIAN OMICRON MENGGUNAKAN ANALISIS KORELASI PEARSON (r)

Noviyanti P (Institut Shanti Bhuana)
Fra Siskus Dian Arianto (Politeknik Negeri Pontianak)
Listra Firgia (Institut Shanti Bhuana)
Benedhikta Kikky Vuspitasari (Institut Shanti Bhuana)



Article Info

Publish Date
31 Dec 2022

Abstract

Corona Virus Disease, which is often known as Covid-19, is a virus whose transmission is very fast and dangerous. Covid-19 then mutated into Covid Omicron. According to WHO, the Covid Omicron variant has been detected in 57 countries (15 December 2021). The emergence of a new variant of Covid, namely Covid Omicron, is a new threat to the world because the spread of this variant of Covid is quite fast compared to other variants. The purpose of conducting this research is to test whether an Expert System using Pearson Correlation Analysis (r) can detect early Covid Omicron. Early detection of Covid Omicron is done by transferring knowledge related to Covid Omicron into a computer, then calculating the correlation (????) between patient data and information data from experts, then analyzing it by determining t_count, comparing t_count with t_table, and concluding the hypothesis from Pearson's correlation analysis ( ) that has been done. Based on the research that has been done, the Covid-19 early detection system using Pearson correlation analysis (r) can provide a link between input variables (x) and output variables (y) with proof through experiments between manual analyzes and system analysis that can provide the same good output.

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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 ...