• Nur Mahmudah Nahdlatul Ulama Sunan Giri University
  • Fetrika Anggraini Nahdlatul Ulama University
Keywords: Bayesian, Gibbs Sampling, Kanker Serviks, MCMC, Regresi Logistik ordinal


Cervical cancer is the most common cancer that causes death in women. This cancer is mainly caused by Human Papilloma Virus (HPV). It is estimated that 52 million of Indonesian women are at risk of having cancer, and 36% of female cancer patients suffer from cervical cancer. This type of cancer cannot be diagnosed immediately as there is several years of pre-malignancy phase; thus, early detection or screening is needed to prevent it from turning into malignant. Pap test as a screening program can detect cancer, precancer, and normal condition. To understand the predicting factors of the test results, a comprehensive mathematical modelling was created using the link function of Bayesian Ordinal Logistic Regression. This study observed several possible factors that may affect Pap test results in Tuban regency, namely Age (X1), Education (X2), Childbirth Experience (X3), Use of Contraceptives (X4), Menstrual Cycle (X5), Age of First Menstruation (X6), History of Miscarriage (X7), Anemia (X8) and Number of Sexual Partners (X9) . The outcomes indicated that the predicting factors of Pap cervical cancer results are Age (X1), Education (X2), Childbirth Experience (X3), Use of Contraceptives (X4), Menstrual Cycle (X5), and Anemia (X8). In this model, there is an inexplainable error dependency as indicated by the varied constance values of alpha.


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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. 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.

F. Y. Aksari and H. B. Notobroto, "Pemodelan Regresi Logistik Backward pada Faktor Risiko Kanker Serviks di Yayasan Kanker Wisnuwardhana Surabaya," Jurnal Biometrika dan Kependudukan, vol. 4, no. 2, p. 152–161, 2015.

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.

. S. Salmah, W. Rajab and E. Djulaeha, "FAKTOR DOMINAN YANG BERHUBUNGAN DENGAN PERILAKU PEMERIKSAAN PAP SMEAR PADA WANITA USIA SUBUR," Jurnal Ilmu dan Teknologi Kesehatan, vol. 1, no. 1, pp. 5-11, 2013.

P. Geng and L. Sakhanenko, "Parameter estimation for the logistic regression model under case-control study," Statistics and Probability Letters, no. 109, pp. 168-177, 2016.

E. Nikita and P. Nikitas , "Sex estimation: a comparison of techniques based on binary logistic, probit and cumulative probit regression, linear and quadratic discriminant analysis, neural networks, and naïve Bayes classification using ordinal variables," International Journal of Legal Medicine, no. 134, p. 1213–1225, 2020.

X. Li and P. Willems, "Probabilistic flood prediction for urban sub-catchments using sewer models combined with logistic regression models," Urban Water Journal, vol. 16, no. 10, p. 687–697, 2019.

A. Aswi , S. Cramb , E. Duncan, W. Hu, G. White and K. Mengersen , "Bayesian Spatial Survival Models for Hospitalisation of Dengue : A Case Study of Wahidin Hospital," International Journal of Environmental Research and Public Health, pp. 1-12, 2020.

M. A. Hasib, L. Khoirunnahar, R. H. B. Rezanur, M. R. Islam and M. K. Hosain, "Classification of malignant and benign tissue with logistic regression," Informatics in Medicine Unlocked, vol. 16, p. 100189, 2019.

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.

W. Li, P. Liu, W. Zhao, Z. Yin and X. Bin, "Effects of preoperative radiotherapy or chemoradiotherapy on postoperative pathological outcome of cervical cancer from the large database of 46,313 cases of cervical cancer in China," European Journal of Surgical Oncology, vol. 46, no. 1, pp. 148-154, 2020.

X. Liu, Applied Ordinal Logistic Regression Using Stata, USA: SAGE, 2015.

F. E. Harrell , Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis, New York: Springer, 2015.

J. M. Hilbe, Practical Guide to Logistic Regression, USA: Taylor & Francis Group, LLC, 2016.

. F. E. Harrell and J. auth, Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis, New York: Springer International Publishing, 2015.

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

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.

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.

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.

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

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.

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.

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

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

O. Martin, Bayesian Analysis with Python, USA: Packt Publishing, 2018.

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

M. Kery, Introduction to WinBUGS for Ecologists, Burlington, USA: Elsevier, 2010.

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

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

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.

J. C. Jesang and C. O. Odhiambo, "Assessing Efficient Risk Ratios: An Application to Surgical Stage Prediction in Cervical Cancer," Open Journal of Statistics, vol. 10, pp. 274-302, 2020.

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