Survival Analysis with Cox Proportional Hazard Model for Tuberculosis (TBC) Patients in Haji Hospital Makassar
Keywords:
Cox Proportional Hazard, Hazard Ratio, Survival Analysis, Tuberculosis
Abstract
Survival analysis is a method in statistics that is used to analyze data with a response variable, namely the time from the start of the observation to the occurrence of an event. One of the objectives of survival analysis is to determine the relationship between the time of occurrence and the factors that are thought to have an influence. One method that can be used is the cox proportional hazard regression method. The data used in this study were inpatient data with tuberculosis at the Haji Makassar Hospital in 2022. TBC data has characteristics that allow it to be analyzed using the cox proportional hazard regression method. The results of the analysis obtained factors that significantly influence the recovery rate of patients with TBC are shortness of breath and smoking habits. The shortness of breath variable has an influence on the recovery rate of TBC patients, namely 0,3506 and the smoking habit variable has an influence on the healing rate of TBC patients, namely 0,7367
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Bustan, M. N., & Poerwanto, B. (2021). Logistic Regression Model of Relationship between Breast Cancer Pathology
Diagnosis with Metastasis. Journal of Physics: Conference Series, 1752(1), 012026. https://doi.org/10.1088/1742-
6596/1752/1/012026
Candrawengi, N. L. P. I., & Irhamah, N. I. (2020). Pemodelan Survival pada Kejadian Demam Berdarah Dengue di Surabaya
Timur dengan Pendekatan Bayesian. Jurnal Sains dan Seni ITS, 9(1), D8–D14.
Chandra, N. E., & Rohmaniah, S. A. (2020). Analisis Survival Model Regresi Semiparametrik pada Lama Studi Mahasiswa.
Jurnal Ilmiah Teknosains, 5(2), 94–98.
Dewi, A. Y., Dwidayati, N. K., & Agoestanto, A. (2020). Analisis Survival Model Regresi Cox dengan Metode MLE untuk
Penderita Diabetes Mellitus. UNNES Journal of Mathematics, 9(1), 31–40.
Dukalang, H. H. (2019). Analisis Regresi Cox Proportional Hazard pada Pemodelan Waktu Tunggu Mendapatkan Pekerjaan.
Jambura Journal of Mathematics, 1(1), 36–42.
Faisal, A. R., Bustan, M. N., & Annas, S. (2019). Analisis Survival dengan Pemodelan Regresi Cox Proportional Hazard
menggunakan Pendekatan Bayesian (Studi Kasus: Pasien Rawat Inap Penderita Demam Tifoid di RSUD Haji
Makassar). VARIANSI: Journal of Statistics and Its application on Teaching and Research, 2(2).
Fajarini, F. A., & Fatekurohman, M. (2019). Analisis Premi Asuransi Jiwa menggunakan Model Cox Proportional Hazard.
Indonesian Journal of Applied Statistics, 1(2), 88.
Fa’rifah, R. Y., & Poerwanto, B. (2019). Platelets and Hematocrit in the Survival Model of Dengue Hemorrhagic Fever (DHF)
Sufferers in Palopo. Materials Science Forum, 967, 3–8. https://doi.org/10.4028/www.scientific.net/MSF.967.3
Istuti, D. M., Manuharawati, & Oktaviarina, A. (2019). Analisis Ketahanan Hidup Data Ties Pasien Tuberkulosis dengan
Metode Exact Likelihood pada Model Regresi Cox Proportional Hazard. Mathunesa: Jurnal Ilmiah Matematika, 7(2).
Kleinbaum, D. G., & Klein, M. (2012). Survival Analysis: A Self-Learning Text (Third Edition). Springer New York.
Liang, C., Zheng, G., Zhu, N., Tian, Z., Lu, S., & Chen, Y. (2011). A new environmental heat stress index for indoor hot and
humid environments based on Cox regression. Building and Environment, 46(12), 2472–2479.
https://doi.org/10.1016/j.buildenv.2011.06.013
Ministry of Health of the Republic of Indonesia. (2022). Indonesia Health Profile 2021. Jakarta: Ministry of Health of the
Republic of Indonesia.
Omurlu, I. K., Ture, M., & Tokatli, F. (2009). The comparisons of random survival forests and Cox regression analysis with
simulation and an application related to breast cancer. Expert Systems with Applications, 36(4), 8582–8588.
https://doi.org/10.1016/j.eswa.2008.10.023
Pertiwi, I. N., & Purnami, S. W. (2020). Regresi Cox Proportional Hazard untuk Analisis Survival Pasien Kanker Otak di CTech Labs Edwar Technology Tangerang. Inferensi, 3(2), 65.
Poerwanto, B., Fa’rifah, R. Y., Sanusi, W., & Side, S. (2018). A matlab code to compute prediction of survival trends in
patients with DHF. Journal of Physics: Conference Series, 1028, 012113. https://doi.org/10.1088/1742-
6596/1028/1/012113
South Sulawesi Health Service. (2021). South Sulawesi Province Health Profile 2021. Makassar: South Sulawesi Province
Health Profile 2021.
Tamara, D. V., Nurhayati, S., & Ludiana. (2022). Penerapan Inhalasi Sederhana Menggunakan Aromaterapi Daun Mint
(Mentha Piperita) terhadap Sesak Nafas pada Pasien TB Paru. Jurnal Cendikia Muda, 2(1), 40–49.
Turkson, A. J., Ayiah-Mensah, F., & Nimoh, V. (2021). Handling Censoring and Censored Data in Survival Analysis: A
Standalone Systematic Literature Review. International Journal of Mathematics and Mathematical Sciences, 2021, 1–
16
Published
2023-10-31
How to Cite
[1]
Z. Nisa, B. Poerwanto, and M. S, “Survival Analysis with Cox Proportional Hazard Model for Tuberculosis (TBC) Patients in Haji Hospital Makassar”, Jurnal Varian, vol. 7, no. 1, pp. 87 - 94, Oct. 2023.
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