Regresi Logistik Backward Elimination pada Risiko Penyebaran Covid-19 di Jawa Timur

Wara Pramesti; Windi Utami; Fenny Fitriani

doi:10.35580/variansiunm26132

Regresi Logistik Backward Elimination pada Risiko Penyebaran Covid-19 di Jawa Timur

Wara Pramesti^(1*), Windi Utami⁽²⁾, Fenny Fitriani⁽³⁾,

(1) Universitas PGRI Adi Buana Surabaya
(2) Universitas PGRI Adi Buana Surabaya
(3) Universitas PGRI Adi Buana Surabaya
(*) Corresponding Author

DOI: https://doi.org/10.35580/variansiunm26132

Abstract

AbstractCorona Virus Disease 2019 or commonly called Covid-19 is a type of virus that can infect the human lungs and can cause fatal diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). East Java Province is one of the provinces in Indonesia that has been exposed to Covid-19 with a high ranking, which is at number 3 in Indonesia (Kompas.com, September 2020), so based on this, of course there are factors that affect the level of risk of spreading the virus. , so we need a model that can be used to determine the factors that are thought to have an effect. The risk of spreading the virus is high, medium and low. The Ordinal Logistics Regression method is one method that can be used to model the factors that are thought to affect the level of risk of the spread of the corona virus in East Java, because ordinal logistic regression has an ordinal-scale response variable according to the level of spread that occurs. The results of the model fit test analysis showed that the logit model was feasible to use. Simultaneous testing of parameter estimates with a value of G2 = 25.64 means that the logit model is simultaneously significant to the response variable. The selection of the backward elimination model shows that the number of Covid-19 deaths and the average household member have a significant effect on the risk of spreading Covid-19 in East Java. The odds ratio for the number of Covid-19 deaths is 1.044. This shows that for every unit increase in the number of Covid-19 deaths, an area with a low or moderate risk status of 1.044 times will become a medium and high risk. The odds ratio value for the average number of households is 0.079, indicating that for every one-unit increase in the average number of households, an area with a low or moderate risk status of 0.079 times will be at medium and high risk. Keywords : Covid-19, Ordinal Regresion Logistic Analysis, Backward Elimination, Odds Ratio

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