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Viona Alliza Diandra Putri
Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro

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ANALISIS LAJU PERBAIKAN KONDISI KLINIS PASIEN COVID-19 DENGAN MENGGUNAKAN PENDEKATAN MULTIPLE PERIOD LOGIT (Studi Kasus: Penderita COVID-19 yang Menjalani Rawat Inap di RSUD Depok Pada September 2021) Viona Alliza Diandra Putri; Sudarno Sudarno; Triastuti Wuryandari
Jurnal Gaussian Vol 11, No 2 (2022): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v11i2.35461

Abstract

Coronavirus Disease-2019, known as Covid-19, is one of infectious diseases that occurred in Wuhan and named as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV 2). This infectious disease is caused by a type of virus groups which can cause disease in animals or humans called Coronavirus. The quality of patient treatment can be seen from time that the patient needs to have clinical improvement and able to get out of the hospital. Survival analysis is a statistical procedure to analyse data with time until a certain event occurs as a response variable One of the methods that can be used is Logit Regression with multiple period logit approach. This research discusses the rate of clinical condition improvement of Covid-19 patients using survival analysis with multiple period logit approach. This logit approach called multiple period logit is used because the predictor variable in this research can change at any time until an event occurs. This research data obtained from medical records at RSUD Depok which are Covid-19 patient data who have been hospitalized in September 2021. The dependent variables consist of the hospitalization length and patient status (cured or censored), while the independent variables consist of age, gender, symptoms, systolic blood pressure, diastolic blood pressure, number of pulse rates, respiration, temperature, saturation, comorbid conditions, and smoking. The data consist of 68 patients which 53 patients go home in better condition. The results of analysis using multiple period logit approach obtained factors that affect the rate of clinical condition improvement of Covid-19 patients, there are age, symptoms, respiration, and congenital disease