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All Journal Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Teknik Informatika Unika Santo Thomas (JTIUST)
Sari, Artini Ratna
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Computer Science & IT Decision Sciences, Operations Research & Management

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Implementasi Penetapan Pasien CBR-AHP Rawat Inap Covid-19 di Rumah Sakit dengan Sumber Daya Terbatas Sari, Artini Ratna; Winarno, Edy
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 2 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

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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.
Implementasi Penetapan Pasien CBR-AHP Rawat Inap Covid-19 di Rumah Sakit dengan Sumber Daya Terbatas Sari, Artini Ratna; Winarno, Edy
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 7 No. 2 : Tahun 2022
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar

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.
Co-Authors Edy Winarno