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Sukma Evadini
Independent Researcher
Computer Science & IT

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Analisis Faktor Risiko Kematian dengan Penyakit Komorbid COVID-19 menggunakan Algoritma ECLAT Sukma Evadini
Jurnal Informasi dan Teknologi 2022, Vol. 4, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v4i1.181

Abstract

The death rate due to infection with the COVID-19 virus is increasing. Throughout 2020, COVID-19 cases continued to increase with a total of 2,995,758 positive cases with a total death toll of 204,987 in more than 213 infected countries. The increasing number of deaths is certainly a problem that needs special attention. One of the factors that can affect the severity of COVID-19 infection is a medical condition. These medical conditions are referred to as comorbid or comorbid conditions. This study aims to analyze the risk factors for death of COVID-19 patients based on comorbid diseases using the Data Mining technique. The algorithm used is ECLAT. The results of this study are age and comorbid diseases have an influence on the patient's condition when discharged from the hospital with a support value of 25% and a confidence value of 100%.
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