Weibull Regression Survival Analysis on the Rate of Recovery of Thyphoid Fever Patients: Case Study of RSUD Haji Makassar

Nurul Maghfira; Bobby  Poerwanto; Hardianti  Hafid

doi:10.36456/jstat.vol17.no2.a9416

Authors

Nurul Maghfira Universitas Negeri Makassar
Bobby Poerwanto Universitas Negeri Makassar
Hardianti Hafid Universitas Negeri Makassar

DOI:

https://doi.org/10.36456/jstat.vol17.no2.a9416

Keywords:

Survival Analysis, weibull regression, Thyphoid Fever

Abstract

Survival analysis is a statistical method used in studying survival related to time, from the beginning of the study to the end of the study. The purpose of survival analysis is to determine the relationship between survival time and independent variables in research that are thought to affect survival time. This study uses weibull regression survival analysis to see the factors that significantly affect the recovery rate of patients with typhoid fever at the Makassar Hajj Hospital in 2022. The results of the analysis of factors that have a significant effect on the rate of recovery of patients with typhoid fever are heartburn. Patients with a history of having heartburn have a hazard ratio value of 1.779, which means that patients with typhoid fever who experience heartburn have a faster recovery rate of 1.779 times compared to patients who do not experience heartburn.

References

Collet David, Modelling Survival Data In Medical Research third Edition. 2013.

R. Y. Fa’rifah and Purhadi, “Analisis Survival Faktor-Faktor yang Mempengaruhi Laju Kesembuhan Pasien Penderita Demam Berdarah Dengue (DBD) di RSU Haji Surabaya dengan Regresi Cox,” Jurnal Sains dan Seni ITS, vol. 1, no. 1, pp. 271–276, 2012.

M. K. Yusuf, “Analisis Survival Lama Waktu Sembuh Dengan Perawatan Standar Pada Pasien Rawat Inap Penyakit Tifus Dengan Menggunakan Metode Regresi Cox Proportional Hazard,” 2018, [Online]. Available: http://search.ebscohost.com/login.aspx?direct=true&db=sph&AN=119374333&site=ehost-live&scope=site%0Ahttps://doi.org/10.1016/j.neuron.2018.07.032%0Ahttp://dx.doi.org/10.1016/j.tics.2017.03.010%0Ahttps://doi.org/10.1016/j.neuron.2018.08.006

A. R. Faisal, M. N. Bustan, and S. Annas, “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, vol. 2, no. 2, p. 62, 2020, doi: 10.35580/variansiunm14629.

H. P. Zhu, X. Xia, C. H. Yu, A. Adnan, S. F. Liu, and Y. K. Du, “Application of Weibull model for survival of patients with gastric cancer,” BMC Gastroenterol, vol. 11, pp. 1–6, 2011, doi: 10.1186/1471-230X-11-1.

L. E. Widyawati and R. D. Bekti, “Analisis Faktor yang Mempengaruhi Laju Kesembuhan Pasien Demam Berdarah Dengue Menggunakan Regresi Cox dan Regresi Weibull (Studi Kasus : Kabupaten Bantul, Yogyakarta),” Jurnal Statistika Industri dan Komputasi, vol. 05, no. 2, p. 26, 2020.

A. Solehah, “Analisis Ketahanan Hidup Pasien Kanker Paru Menggunakan Regresi Weibull,” 2018.

Y. Levani and A. D. Prastya, “Demam Tifoid: Manifestasi Klinis, Pilihan Terapi Dan Pandangan Dalam Islam,” Al-Iqra Medical Journal : Jurnal Berkala Ilmiah Kedokteran, vol. 1, no. 2, pp. 10–16, 2020, doi: 10.26618/aimj.v3i1.4038.

Juniah and M. Arianti, “Pentingnya Pengetahuan Kesehatan Demam Typhoid Anak,” Jurnal Pengabdian Masyarakat, vol. 2, no. 1, pp. 7–14, 2023, doi: 10.59030/jpmbd.v2i1.18.

S. Khairunnisa, E. M. Hidayat, and R. Herardi, “Hubungan Jumlah Leukosit dan Persentase Limfosit terhadap Tingkat Demam pada Pasien Anak dengan Demam Tifoid di RSUD Budhi Asih Tahun 2018 – Oktober 2019,” Seminar Nasional Riset Kedokteran (SENSORIK), pp. 60–69, 2020.

M. Sopiyudin Dahlan, Analisis Survival Dasar-Dasar Teori Dan Aplikasi Program Stata. Jakarta: Sagung Seto, 2013.

N. H. Hasa, M. N. Bustan, and Aswi, “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 ISSN 2684-7590 (Online) Vol. 4 No. 1 (2022), 1-8, vol. 4, no. 1, pp. 1–8, 2022.

I. Sari, “Analisis Regresi Weibull (Kasus: Faktor-faktor yang mempengaruhi laju kesembuhan penderita penyakit demam berdarah dengue di RSAL JALA AMMARI Makassar),” 2017.

Yogi Adam Firdaus, N. Ngatini, and Sekarsari Utami Wijaya, “Pemodelan Regresi Data Panel Harga Beras di Wilayah Indonesia Bagian Barat,” J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika, vol. 16, no. 2, pp. 486–498, Dec. 2023, doi: 10.36456/jstat.vol16.no2.a8061.

C. H. Imanina, “ANALISIS SURVIVAL TERHADAP PASIEN PENYAKIT GINJAL KRONIS DENGAN MENGGUNAKAN COX REGRESSION (Studi Kasus: Pasien Penyakit Ginjal Kronis di RSUD Arifin Achmad, Pekanbaru, Riau),” no. 21, pp. 1–9, 2018.

G. Anuraga, A. Indrasetianingsih, and M. Athoillah, “Pelatihan pengujian hipotesis statistika dasar dengan software r,” BUDIMAS: Jurnal Pengabdian Masyarakat, vol. 3, no. 2, pp. 327–334, 2021.

Riangkaryaman, “MODEL SEMIPARAMETRIK COX PH DAN PARAMETRIK (WEIBULL DAN LOGNORMAL) DALAM ANALISIS S