Jurnal Sistim Informasi dan Teknologi
2023, Vol. 5, No. 2

Sistem Pendukung Keputusan dengan Metode Profile Matching dalam Mengidentifikasi Gejala Awal Penderita COVID-19

Jelviana Risa (Sekolah Dasar Negeri 26 Kinali)



Article Info

Publish Date
05 Sep 2022

Abstract

The COVID-19 pandemic has not yet subsided, this outbreak has spread to almost all countries in the world, the initial symptoms of sufferers caused by acute respiratory distress coronavirus 2 (SARS-CoV-2). Symptoms of COVID-19 that can be transmitted from human to human, when one person is exposed to signs of a contagious COVID-19 occurring in the community is not the right attitude and action but panic and worry. The initial symptoms of COVID-19 have criteria that identify the initial symptoms of COVID-19, which are 10 (ten) criteria consisting of fever, cough and sore throat, fatigue, loss of smell and taste, joint and muscle pain, headache, diarrhea, shortness of breath. breath, nausea, vomiting, and nasal congestion. The purpose of this study was to identify the early symptoms of COVID-19 sufferers. This research was conducted through processing data on COVID-19 patients sourced from UPT Puskemas VI Koto Selatan, based on the results of the identification of symptoms of COVID-19 in patients carried out by health workers on duty at UPT Puskesmas VI Koto Selatan, then the data was processed using Support System Software. The decision to know the early symptoms of COVID-19. Furthermore, mathematical calculation techniques are also used to see the accuracy results. The method used to determine the initial symptoms in patients with COVID-19 is the Profile Matching method. The results of this study there were 6 patients from 8 test data that had the same decisions generated by the system, therefore the conclusion from this study was the results of the Decision Support System testing that had been carried out in identifying the initial symptoms of COVID-19 sufferers at UPT Puskemas VI South Koto overall there are 75% of patient data indicated by COVID-19 and 25% of patient data not indicated by COVID-19

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Journal Info

Abbrev

JSisfotek

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management

Description

The Jurnal Sistim Informasi dan Teknologi (JSISFOTEK) aims to publish manuscripts that explore information systems and technology research and thus develop computer information systems globally. We encourage manuscripts that cover the following topic areas: - Analytics, Business Intelligence, and ...