Ummu Athifah, Tifa (2021) SURVIVAL TIME DATA MODELING FOR DIABETICS DURING THE COVID 19 PANDEMIC USING SEVERAL SENSITIVE DISTRIBUTIONS (WEIBULL, GAMMA, AND NORMAL LOGS). SURVIVAL TIME DATA MODELING FOR DIABETICS DURING THE COVID 19 PANDEMIC USING SEVERAL SENSITIVE DISTRIBUTIONS (WEIBULL, GAMMA, AND NORMAL LOGS), 15 (15). pp. 717-724. ISSN 1314-7552

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Abstract

The Covid-19 pandemic has changed lifestyle and caused an increase in the death rate of diabetic patients. This is because diabetes mostly occurs due to high-stress levels, changes in food consumption patterns (fast food), and lack of exercise. Therefore, this research aims to determine the mortality probability of survival time data for diabetic patients. The comparison of several probability models was subsequently grouped according to their data sensitivity, namely the exponential distribution probability model, Gamma, Log-Normal, and Weibull, due to extreme events such as the Covid-19 pandemic. The graphical methods such as CDF and PDF plots were used to determine the best probability model to analyze the pattern of survival time for 50 diabetic patients at the Mandau Regional General Hospital (RSUD) Bengkalis Regency, Riau Province. The results showed that the Weibull model was the best in approaching the given observation data. This was also supported by numerical models such as AIC and BIC, by giving the smallest values for the two numerical methods compared to other probability models

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