Jurnal Teknik Informatika Unika Santo Thomas (JTIUST)
Vol 7 No. 2 : Tahun 2022

Implementasi Penetapan Pasien CBR-AHP Rawat Inap Covid-19 di Rumah Sakit dengan Sumber Daya Terbatas

Sari, Artini Ratna (Unknown)
Winarno, Edy (Unknown)



Article Info

Publish Date
01 Feb 2023

Abstract

Covid-19 is one of the most dangerous and number one killer viruses in the world today and cannot be handled properly. Covid-19 patients with mild symptoms do not require hospitalization unless there are concerns about the possibility of a rapid worsening and according to medical considerations. Patients who are elderly and have comorbid diseases have a greater risk of experiencing more severe symptoms and experiencing death, so they can be considered for treatment. To make it easier to determine inpatients for COVID-19 patients, an expert system with the CBR-AHP method is needed. This system can be used to conduct consultations on Covid-19 disease and provide solutions for the treatment of the type of Covid-19 disease found where the consultation results are obtained from the highest Nei&Li similarity value. Of all the variants found above, the highest Nei&Li similarity value is Omicron with a similarity of 1,000. The system for determining the inpatient status of Covid-19 patients in hospitals with the Nei&Li algorithm will recommend Covid-19 diseases found with similarity above 0.5 and similarity below 0.5 will be entered into the review table to find a solution.

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Journal Info

Abbrev

JTIUST

Publisher

Subject

Computer Science & IT

Description

Terbit Setiap Bulan Juni dan Desember setiap Tahunnya. Jurnal ini Media publikasi untuk bidang Ilmu Komputer seperti Fuzzy Logic, Teknologi dan Jaringan, Robotika, Komputasi, Mikrokontroller, Arsitektur Komputer, Sistem Cerdas, Rekayasa Web dan Mobile, Sistem Terdistribusi, Sistem Kontrol, Data ...