bit-Tech
Vol. 4 No. 3 (2022): bit-Tech

Aplikasi Pendeteksi Penyakit Bawaan Untuk Pencegahan Covid 19 Berbasis Mobile

Satria Abadi (Unknown)
Riki Riki (Universitas Buddhi Dharma)
Ade Layla Fitriani (STMIK Pringsewu)



Article Info

Publish Date
09 Jun 2022

Abstract

Coronavirus disease (Covid19) is an infectious disease caused by the SARSCoV2 virus. Most people infected with COVID-19 show mild to moderate symptoms and recover without specific treatment. However, around 4,444 people are seriously ill and need to see a doctor. The purpose of using information technology to create a comorbid population identification system is to create a classification model for residents with congenital diseases for the prevention of Covid19. This study aims to identify people who have comorbidities using information technology according to evidence of congenital disease. The system development method used is the waterfall method. This survey flow describes the stages or survey procedures of the Covid19 classification application which aims to facilitate the classification of residents with congenital diseases. The result find is an application system or website for the classification of disease detection using a mobile website. This website can classify or classify diseases based on the characteristics and criteria of the disease. When conducting tests, this website facilitates and assists in accessing disease data, especially congenital and chronic diseases. According to the results of this website, it is easy for them to see the name of the disease and the symptoms they are suffering from as a form of preventing the transmission of Covid-19.

Copyrights © 2022






Journal Info

Abbrev

bt

Publisher

Subject

Computer Science & IT

Description

The bit-Tech journal was developed with the aim of accommodating the scientific work of Lecturers and Students, both the results of scientific papers and research in the form of literature study results. It is hoped that this journal will increase the knowledge and exchange of scientific ...