Abstract
<p align="justify">Chronic kidney disease is a disease whose risk of death is always increasing. This disease was ranked as the 13th leading cause of death in Indonesia in 2017. One of the successful managements of chronic kidney disease can be seen from the possibility of survival of patients with chronic kidney disease. To identify the probability of survival of an object, survival analysis is used. One method of survival analysis that can be used to determine the survival time of patients with chronic kidney disease is Cox regression. Cox regression must satisfy the proportional hazard assumption, where the ratio of the two hazard values must be constant with time. The graphical method, namely the log-log graph, can be used to test the proportional hazard assumption, but the results are only used as a provisional estimate. In this study, the goodness of fit test was used to test the assumptions by calculating the correlation between the Schoenfeld residuals and the survival time rank. In conclusion, the variables of hypertension and haemodialysis frequency meet the proportional hazard assumption.</p><p align="justify"><strong>Keywords: </strong>chronic kidney disease; Cox regression; goodness of fit; log-log graph; proportional hazard assumption</p>
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