Analisis Ketahanan Hidup Pasien Kanker Paru Menggunakan Regresi Weibull

Arivatus Solehah, Mohamat Fatekurohman


Lung cancer is one of the diseases which difficult to detect because of uneasy symptoms detection till it develops being the risky one. But, if the disease has been found, it can spread fast and cause death. According to the data of WHO, the type of cancer which causes the most of death is lung cancer which reaches 1,3 milion death per year. Therefore, a survival analysis will be conducted to determine factors that affect the survival of lung cancer patient by using Weibull regression. The result shows some factors that significantly influence the survival of lung cancer patient are gender, erythrocyte, and general condition.


Keywords : lung cancer; survival analysis; Weibull regression

Full Text:



Hashemi, A., Pilevar, A.H., and Rafeh, R. Mass Detection in Lung CT Images Using Region Growing Segmentation and Decision Making Based on Fuzzy Inference System and Artificial Neural Network. I.J. Image, Graphics and Signal Processing. Vol 6: 16-24. 2013.

Hulma, M.A., Basyar, M., dan Mulyani, H. Hubungan Karakteristik Penderita dengan Gambaran Sipatologi Pada Kasus Karsinoma Paru yang Dirawat di RSUD Dr. M. Jamil Padang. Jurnal. 3 (2): 196-201. 2014.

Collet, D. Modelling Survival Data In Medical Research. ed. London: Chapman and Hall. 2003.

Monica, A.S.Y. dan Purhadi. Analisis Faktor yang Mempengaruhi Laju Kesembuhan Pasien Tuberkulosis Paru di RSUD Dr. Soetomo Tahun 2015 Menggunakan Regresi Weibull dan Regresi Cox Proportional Hazard. Jurnal Sains dan Seni ITS. 2 (5): 2337-3520. 2016.

Fatekurohman, M., Nurmala. N., and Anggraini. D. Comparison of exact, efron and breslow parameter approach method on hazard ratio and stratified cox regression model. Journal of Physics Conference Series, 1008012007. doi: 10.1088/1742-6596/1008/1/012007. 2018.

Kleinbaum, D.G. and Klein, M. Survival Analysis a Self-Learning Text Third Edition. New York: Springer. 2012.


  • There are currently no refbacks.