APLIKASI KOMPUTASI BAYESIAN REGRESI DUMMY PADA KASUS KANKER SERVIKS DI KABUPATEN TUBAN

Cervical cancer is the most common cancer suffered by women and is the cause of death. The leading
cause of cervical cancer is infection with Human Papilloma Virus (HPV). Cervical cancer is a disease caused
by the growth of body tissue cells that are not normal in the cervix contained in the reproductive organs of a
woman's body and cause death. A screening program is needed for the length of hospitalization for cervical
cancer patients to prevent the emergence of a malignant phase. This study aims to determine the factors that
affect the length of stay of cervical cancer patients in Tuban Regency using the Bayesian Regression Dummy
computational method. The Bayesian method is a computational technique in parameter estimation that
combines the likelihood function and prior distribution into a posterior distribution in estimating model
parameters. Bayesian dummy regression produces a variable that significantly affects the length of stay of
cervical cancer patients, namely the Complications variable (X1). An alpha value of 2.17 shows that some
dependencies/errors cannot be explained in the dummy regression model in the case of cervical cancer
hospitalization in the Tuban Regency