Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorSetiawan, Adi-
dc.contributor.advisorParhusip, Hanna Arini-
dc.contributor.authorPradani, Wynona Adita-
dc.description.abstractIn 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.en_US
dc.subjectpositive patients with COVID-19 in Indonesiaen_US
dc.subjectGrowth Modelen_US
dc.subjectBootstrap Methoden_US
dc.subjectLog-logistic 3 Parametersen_US
dc.titleAnalisis Regresi Non Linear pada Data Pasien COVID-19 Menggunakan Metode Bootstrapid
uksw.facultyFakultas Sains dan Matematika-
Appears in Collections:T1 - Mathematics

Files in This Item:
File Description SizeFormat 
T1_662016023_Judul.pdf933.63 kBAdobe PDFView/Open
T1_662016023_BAB I.pdf
  Until 2999-01-01
335.91 kBAdobe PDFView/Open Request a copy
T1_662016023_BAB II.pdf
  Until 2999-01-01
526.57 kBAdobe PDFView/Open Request a copy
T1_662016023_BAB III.pdf
  Until 2999-01-01
569.04 kBAdobe PDFView/Open Request a copy
T1_662016023_BAB IV.pdf1.16 MBAdobe PDFView/Open
T1_662016023_BAB V.pdf
  Until 2999-01-01
348.71 kBAdobe PDFView/Open Request a copy
T1_662016023_Daftar Pustaka.pdf453.9 kBAdobe PDFView/Open
  Until 2999-01-01
1.01 MBAdobe PDFView/Open Request a copy

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.