Aplikasi Komputasi Bayesian Regresi Dummy Pada Kasus Kanker Serviks di Kabupaten Tuban

Abstract View: 391, PDF Download: 347

Authors

  • Nur Mahmudah Universitas Nahdlatul Ulama Sunan Giri
  • Pelangi Eka Yuwita Universitas Nahdlatul Ulama Sunan Giri

DOI:

https://doi.org/10.32665/james.v5i2.415

Keywords:

Bayesian, Kanker Serviks, Regresi Dummy, Cervical Cancer, Dummy Regression

Abstract

Kanker serviks adalah kanker yang paling banyak diderita oleh wanita yang menjadi penyebab kematian. Penyebab utama kanker serviks adalah infeksi Human Papilloma Virus (HPV). Kanker serviks merupakan penyakit yang disebabkan oleh pertumbuhan sel- sel jaringan tubuh yang tidak normal di dalam leher rahim/ serviks yang terdapat dalam organ bagian reproduksi pada tubuh wanita dan menyebabkan kematian. Untuk mencegah munculnya fase ganas dibutuhkan program screening pada lama rawat inap pasien kanker serviks. Penelitian ini bertujuan untuk mengetahui faktor-faktor yang mempengaruhi lama rawat inap pasien kanker serviks di Kabupaten Tuban dengan metode komputasi Bayesian Regresi Dummy. Metode Bayesian adalah salah satu teknik komputasi pada estimasi parameter yang menggabungkan fungsi likelihood dan distribusi prior menjadi distribusi posterior dalam menduga parameter model. Bayesian regresi dummy menghasilkan suatu variabel yang memiliki pengaruh signifikan terhadap lama rawat inap pasien kanker serviks, yaitu variabel Komplikasi (X1). Dengan nilai alpha 2.17, menunjukan bahwa terdapat dependensi/error yang tidak bisa dijelaskan dalam model regresi dummy pada kasus lama rawat inap kanker serviks di Kabupaten Tuban.

References

S. Wahyuni, "Faktor-faktor yang mempengaruhi perilaku deteksi dini kanker serviks di kecama-tan ngampel kabupaten kendal jawa tengah," Jurnal Keperawatan Maternitas, vol. I, no. 1, pp. 55-60, 2013.

J. Wang, K. M. Elfström, B. Andrae and S. N. Kleppe, "Cervical cancer case–control audit: Results from routineevaluation of a nationwide cervical screening program," nternational Journal of Cancer, no. 146, p. 1230–1240 , 2019.

R. M. Nugrahani and M. Salamah, "Analisis Faktor-Faktor yang Mempengaruhi Hasil Pap Test Kanker Serviks dengan Menggunakan Metode Regresi Logistik Ordinal," JURNAL SAINS DAN SENI ITS, pp. 16-19, 2012.

S. N. Aulele, H. M. Patty and Trisnawaty, "ANALISIS FAKTOR-FAKTOR YANG MEMPERNGARUHI KANKER LEHER RAHIM DI KOTA AMBON DENGAN MENGGUNAKAN REGRESI LOGISTIK BINER," Jurnal Ilmu Matematika dan Terapan, vol. 10, no. 1, p. 61–68, 2016|.

F. s. insani, S. Af and L. Talangko, "Metode Bootstrap Aggregating Regresi Logistik untuk Peningkatan Ketepatan Klasifikasi Regresi Logistik Ordinal," J. Stat. UNHAS, pp. 1-9, 2015.

L. Fahrmeir, . T. Kneib, S. Lang and B. Marx, Regression Models, Methods and Applications, New York: Springer-Verlag Berlin Heidelberg, 2013.

N. Wu, i. (. Song, R. Yao, . Q. Yu, . C. Tang and . S. Zhao, "A Bayesian sample selection model based on normal mixture to investigate household car ownership and usage behavior," Travel Behaviour and Society, pp. 36-50, 2020.

W. M. Bolstad and J. M. Curran, Introduction to Bayesian Statistics, Canada: John Wiley & Sons, 2017.

N. Han and . R. J. Ram, "Bayesian modeling and computation for analyte quantification in complex mixtures using Raman spectroscopy," Computational Statistics and Data Analysis, pp. 1-19, 2019.

Y. F. Aksari and H. . B. Notobroto, "Pemodelan Regresi Logistik Backward pada Faktor Risiko Kanker Serviks di Yayasan Kanker Wisnuwardhana Surabaya," Jurnal Biometrika dan Kependudukan, pp. 152-161, 2015.

Y. Fan, D. Nott, M. S. Smith and e.-L. Dortet-Bernadet, Flexible Bayesian Regression Modelling, USA: Academic Press, 2019.

P. Ismartini, "Pengembangan Model Liniear HIrarki Dengan Pendekatan Bayesian Untuk Pemodelan Data Pengeluaran Data Pengeluaran Perkapita Rumah Tangga," Jurusan Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Sepuluh Nopember, Surabaya, 2013.

N. Mahmudah and H. Pramoedyo, "Spatial Modeling Weibull-3 Survival Parameters with Frailty Distributed Conditionally Autoregressive (CAR)," Natural B, Journal of Health and Environmental Sciences, vol. 1, no. 3, pp. 93-102, 2015.

N. Mahmudah and F. Anggraini, "Bayesian Survival Dagum 3 Parameter Link Function Models in the Suppression of Dengue Fever in Bojonegoro," IAENG International Journal of Applied Mathematics, vol. 51, no. 3, pp. 1-7, 2021.

G. E. Box and G. C. Tiao, Bayesian Inference in Statistical Analysis, Reading,MA : Addison-wesley, 1973.

I. Ntzoufras, Bayesian Modeling Using WinBUGS, USA: John Wiley & Sons, Inc, 2009.

D. Darmofal, "Bayesian Spatial Survival Models for Political Event Processes," Department of Political, Science University of South Carolina. 350 Gambrell Hal. Columbia, 2008.

N. Mahmudah, "Analisis Survival Weibull 3p Menggunakan Aplikasi Winbugs," Jurnal Mahasiswa Statistik, vol. 2, no. 3, pp. 237-240, 2014.

h. Yang and . S. J. Novick, Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies, New York: CRC Press, 2019.

N. Mahmudah, N. Iriawan and S. W. Purnami, "Bayesian Spatial Survival Models for HIV/AIDS Event Processes in East Java.," Indian Journal of Public Health Research & Development, vol. 9, no. 11, 2018.

B. L. D, Bayesian analysis of time series, USA: Chapman & Hall/CRC, 2019.

S. M. Lynch, Introduction to Applied Bayesian Statistics and Estimation for Social Scientists, New York: Springer, 2017.

J. V. Stone, Bayes Rule with R A Tutorial Introduction to Bayesian Analysis, New York: Sebtel Press, 2016.

J. Kruschke, Doing Bayesian Data Analysis, USA: Elsevier Science Academic Press, 2014.

S. Banerjee, M. M. Wall and B. P. Carlin, "Frailty modeling for spatially correlated survival data, with application to infant mortality in Minnesota," Biostatistics, pp. 123-142, 2003.

Z. Zhang, J. Zhang , J. Lu and J. Tao, "Bayesian Estimation of the DINA Model With Pólya-Gamma Gibbs Sampling," Frontiers In Psychology, vol. 11, no. 384, pp. 1-15, 2020.

N. Mahmudah and S. Sukono, "Bayesian Regresi Survival Pada Proses Kejadian HIV/AIDS Di Jawa Timur," Jurnal Matematika Sains dan Teknologi (JMST), vol. 21, no. 2, pp. 111-123, 2020.

B. Puza, Bayesian Methods for Statistical Analysis, Australia: ANU Press, 2017.

Downloads

Published

2022-08-23

How to Cite

[1]
N. Mahmudah and P. E. Yuwita, “Aplikasi Komputasi Bayesian Regresi Dummy Pada Kasus Kanker Serviks di Kabupaten Tuban”, JaMES, vol. 5, no. 2, pp. 93–99, Aug. 2022.

Issue

Vol. 5 No. 2 (2022): Journal of Mathematics Education and Science

Section

Articles

License

Copyright (c) 2022 Journal of Mathematics Education and Science

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
Abstract View: 391, PDF Download: 347