ON COMPUTATIONAL BAYESIAN ORDINAL LOGISTIC REGRESSION LINK FUNCTION IN CASES OF CERVICAL CANCER IN TUBAN

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 cann...

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Main Authors: Nur Mahmudah, Fetrika Anggraini
Format: Article
Language:English
Published: Universitas Pattimura 2022-09-01
Series:Barekeng
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Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5973
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author Nur Mahmudah
Fetrika Anggraini
author_facet Nur Mahmudah
Fetrika Anggraini
author_sort Nur Mahmudah
collection DOAJ
description 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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publishDate 2022-09-01
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spelling doaj-art-e4176ad470da456b9ab7774c17fd66ff2025-08-20T03:36:12ZengUniversitas PattimuraBarekeng1978-72272615-30172022-09-0116390991810.30598/barekengvol16iss3pp909-9185973ON COMPUTATIONAL BAYESIAN ORDINAL LOGISTIC REGRESSION LINK FUNCTION IN CASES OF CERVICAL CANCER IN TUBANNur Mahmudah0Fetrika Anggraini1Nahdlatul Ulama Sunan Giri UniversityNahdlatul Ulama UniversityCervical 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.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5973bayesiangibbs samplingkanker serviksmcmcregresi logistik ordinal
spellingShingle Nur Mahmudah
Fetrika Anggraini
ON COMPUTATIONAL BAYESIAN ORDINAL LOGISTIC REGRESSION LINK FUNCTION IN CASES OF CERVICAL CANCER IN TUBAN
Barekeng
bayesian
gibbs sampling
kanker serviks
mcmc
regresi logistik ordinal
title ON COMPUTATIONAL BAYESIAN ORDINAL LOGISTIC REGRESSION LINK FUNCTION IN CASES OF CERVICAL CANCER IN TUBAN
title_full ON COMPUTATIONAL BAYESIAN ORDINAL LOGISTIC REGRESSION LINK FUNCTION IN CASES OF CERVICAL CANCER IN TUBAN
title_fullStr ON COMPUTATIONAL BAYESIAN ORDINAL LOGISTIC REGRESSION LINK FUNCTION IN CASES OF CERVICAL CANCER IN TUBAN
title_full_unstemmed ON COMPUTATIONAL BAYESIAN ORDINAL LOGISTIC REGRESSION LINK FUNCTION IN CASES OF CERVICAL CANCER IN TUBAN
title_short ON COMPUTATIONAL BAYESIAN ORDINAL LOGISTIC REGRESSION LINK FUNCTION IN CASES OF CERVICAL CANCER IN TUBAN
title_sort on computational bayesian ordinal logistic regression link function in cases of cervical cancer in tuban
topic bayesian
gibbs sampling
kanker serviks
mcmc
regresi logistik ordinal
url https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5973
work_keys_str_mv AT nurmahmudah oncomputationalbayesianordinallogisticregressionlinkfunctionincasesofcervicalcancerintuban
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