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Harbianti Harbianti
Program Studi Matematika, Fakultas SAINS, Universitas Cokroaminoto Palopo, Palopo, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

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Analisis Model Cox Proportional Hazard dan Regresi Logistik sebagai Upaya Pencegahan Covid-19 di Kota Palopo Avini Avini; Krisna Wansi Patunduk; Sumarni Sumarni; Harbianti Harbianti; Ananda Pratiwi; Rahmat Hidayat
Inferensi Vol 5, No 2 (2022)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v5i2.14064

Abstract

This study focused on Covid-19 patients in Palopo City. This study aims to model the recovery time of Covid-19 patients in the city of Palopo. The variables used are factors that are thought to affect the survival period of Covid-19 patients. The instrument used in this study is secondary data obtained from the Palopo City Health Office. The data analysis used in this study is the Cox proportional hazard method to determine the relationship between the dependent variable and the independent variable and the Logistics Regression method, which is the analytical method used to see the relationship between nominal or ordinal predictor variables as well as intervals or ratios. The results of the research carried out are the Cox proportional hazard method analysis states that the variable fever symptom significantly affects the survival of Covid-19 patients in Palopo city with a significance level of 1 time greater than the other variables. Analysis of the logistic regression method states that the fever symptom variable has a significant effect on the survival time of Covid-19 patients in Palopo City. Furthermore, based on the results of the comparison of AIC values it is stated that the best model that can be used to model the survival rate of covid-19 patients in Palopo city is the cox model proportional hazard.
Co-Authors Ananda Pratiwi Avini Avini Krisna Wansi Patunduk Rahmat Hidayat Sumarni Sumarni