Penerapan Metode Regresi Logistik Biner terhadap Faktor Risiko Kematian Akibat Covid-19 di RSUP H. Adam Malik Medan

Abstract

The COVID-19 pandemic is a global phenomenon that is in the limelight, because of its very fast spread and can hardly be avoided by various countries. In Indonesia, the highest number of daily cases based on JHU CSSE COVID-19 Data, occurred on February 16, 2022, which was 64,718 cases. Meanwhile, the highest death rate in Indonesia occurred on August 10, 2021, which was 2,048 cases. This is certainly a concern for many people about how and what are the factors causing the death rate due to COVID-19. This study aims to find out the factors that are most at risk of death from COVID-19. Factors to be studied include: gender, age, congenital diseases, length of treatment, respiratory frequency, and blood pressure of the patient. The data used in this study is secondary data obtained from the results of medical records of COVID-19 patients who were hospitalized at RSUP H. Adam Malik Medan as many as 90 people. The data analysis technique used is binary logsistic regression analysis. The results of binary logistic regression analysis are known from the 6 variables studied, there are only 4 variables that have a significant effect on deaths due to COVID-19. These variables are congenital diseases (x3), duration of treatment (x4), respiratory frequency (x5), and blood pressure (x6). The logistic regression model obtained is as follows. In[n(x)1−n(x)]=−1,739+2,057x3−1,558x4−1,983x5+1,948x6 So the most risky factor for death from COVID-19 is the congenital disease factor.