ANALISIS BAYESIAN SURVIVAL WEIBULL UNTUK MENENTUKAN FAKTOR YANG MEMPENGARUHI LAJU KESEMBUHAN PASIEN RAWAT INAP KANKER SERVIKS DI RSDU KOTA MAKASSAR
Keywords:
Survival Analysis, Bayesian Weibull, Cervical Cancer
Abstract
Survival analysis is a statistical procedure for analyzing data where the response variable is the time until the occurrence of an event. In this study, Bayesian survival Weibull was used to determine the factors that influence the rate of recovery of cervical cancer inpatients. The data used in this study is cervical cancer inpatient data at the Makassar City Hospital for the 2017-2019 period. Based on the results of the analysis, it was found that a significant factor affecting the healing rate of cervical cancer inpatients was complications. Cervical cancer inpatients who experience complications tend to recover slower by 0.258 than patients who do not experience complications.
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Septi, Y., Monica, A., & Purhadi. (2016). 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, 2337-3520.
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American Cancer Society, (2020). Cancer Fact and Figure 2020.
Aswi, A., Cramb, S., duncan, E., Hu, W., White, G., & Mengersen, k. (2020). Bayesian Spatial Survival Model for Hospitalisations of dangue : A case Study of Wahidin Hospital in Makassar, Indonesia. International Journal of Environmental Research and Public Health, 878.
Casella, B. P., & George, E. I. (1992). The America Statistical Association. In Explaining Gibbs Sampler (pp. 167-174).
Dahlan, M. N. (2013). Analisis Survival "dasar-dasar Teori dan Aplikasi Program Stata". Jakarta: Sagung Seto.
Harlan, J. (2017). Analisis Survival . Depok: Gunadarma .
Inayati, K. d., & Purnami, S. W. (2015). Analisis Survival Nornparametrik Pada Pasien Kanker Serviks di RSUd dr. Soetomo Surabaya Menggunakan Metode Kaplan Meier dan Uji Log Rank. Jurnal Sains dan Seni ITS, 2337-3520.
Kleinbaum, D. G., & Klein, M. (2005). Survival Analysis A Self-Learning Text. New York: Springer Science+Business Media, Inc.
Lee, E. T., & Wang, J. W. (2003). Statistical Methods for Survival data Analysis. Oklahoma: John Wiley & Sons.
Mufidah, A. S., & Purhadi. (2016). Analisis Survival Pada Pasien Demam Berdarah (DBD) di RSU Haji Surabaya Menggunakan Model Regresi Weibull. Jurnal Sains dan Seni ITS, 2337-3520.
Septi, Y., Monica, A., & Purhadi. (2016). 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, 2337-3520.
Thamrin, S. A., Azhar, & Jaya, A. K. (2018). Penaksiran Parameter distribusi weibull dengan Metode Bayesian Survival dan Maksimum Likelihood. Jurnal Keteknikan dan Sains (JUTEKS), 2621-7376.
WHO. (2018). Cervix uteri fact sheet. Diakses dari http://gco.iarc.fr/ today/data/ factsheets/cancers/23-Cervix-uteri-fact-sheet.pdf
Published
2022-06-03
How to Cite
Hasa, N. H., Bustan, M. N., & Aswi, A. (2022). ANALISIS BAYESIAN SURVIVAL WEIBULL UNTUK MENENTUKAN FAKTOR YANG MEMPENGARUHI LAJU KESEMBUHAN PASIEN RAWAT INAP KANKER SERVIKS DI RSDU KOTA MAKASSAR. VARIANSI: Journal of Statistics and Its Application on Teaching and Research, 4(1), 1-8. https://doi.org/10.35580/variansiunm6
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