Please use this identifier to cite or link to this item: https://repository.uksw.edu//handle/123456789/23777
Title: Analisis Regresi Non Linear pada Data Pasien COVID-19 Menggunakan Metode Bootstrap
Authors: Pradani, Wynona Adita
Keywords: positive patients with COVID-19 in Indonesia;Growth Model;parameters;Bootstrap Method;Log-logistic 3 Parameters
Issue Date: 4-May-2021
Abstract: In this study, it discusses non-linear regression analysis modeling using statistical data on the development of patients who have tested positive for the Covid-19 virus in Indonesia. The Covid-19 virus is very easy to spread because the virus is so contagious which WHO (World Health Organization) declared this disease as pandemic, so this study uses data of patient who tested positive for Covid-19 in Indonesia using five non-linear regression analysis models, called Weibull 3 parameters, Gompertz 3 parameter model, Log-logistic 3 parameter model, Log-logistic 4 parameter model and Logistic 3 parameters model. The best analysis in predicting the Log-logistic 3-parameter model is with AIC = 6527.434 and RMSE = 6836.79, and the parameter values obtained in the Log-logistic 3-parameter model, is and A = 19477000, so that parameter estimation using the Bootstrap method B = 10000 by using the 95% confidence interval for the parameter and A value, respectively, are , so that the average Bootstrap estimation value , and are obtained. In the prediction data of patients who tested positive for Covid-19 in Indonesia compared to the observational data from the comparison results, the MAPE value = 9% was obtained, so it can be said that the Log-logistic 3 parameter modeling is very good in predicting.
URI: https://repository.uksw.edu/handle/123456789/23777
Appears in Collections:T1 - Mathematics

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