Analisis Faktor-Faktor Yang Memperngaruhi Kanker Leher Rahim Di Kota Ambon Dengan Menggunakan Regresi Logistik Biner

Abstract

AbstrakKanker serviks atau kanker leher rahim adalah jenis penyakit kanker yang terjadi pada daerah leher rahim, yaitu bagian rahim yang terletak di bawah yang membuka ke arah liang vagina. Berawal dari leher rahim, apabila telah memasuki tahap lanjut, kanker ini bisa menyebar ke organ-organ lain di seluruh tubuh. Regresi logistik biner merupakan salah satu pendekatan model matematis yang digunakan untuk menganalisis hubungan beberapa faktor dengan sebuah variabel yang bersifat dikotomus (biner). Tujuan dari penelitian ini adalah menentukan faktor-faktor yang mempengaruhi penyebab kanker leher rahim di kota Ambon dengan menggunakan regresi logistik biner. Hasil penelitian menunjukan bahwa faktorfaktor yang mempengaruhi kanker leher rahim di kota Ambon dengan menggunakan regresi logistik biner adalah usia ( 1 ) dan frekuensi menikah ( 4 ) dengan ketepatan pengklasifikasian penderita dan non penderita kanker leher rahim berturut-turut adalah 57,14% dan 66,67%. Secara keseluruhan, model regresi logistik yang telah diperoleh dapat mengklasifikasikan responden sebesar 61,9%. AbstractCervical cancer is a type of cancer that occurs in the cervical region that is part of the uterus that is located under the opening to the vagina. Starting from the cervix if it has entered the stage, this cancer can spread to other organs throughout the body. Binary logistic regression is one approach used a mathematical model to analyze the relationship of several factors with a variable is dichotomous (binary). The purpose of this study is to determine the factors that influence the cause of cervical cancer in the city of Ambon by using binary logistic regression. The results showed that the factors that affect cervical cancer in the city of Ambon by using binary logistic regression are age ( 1 ) and frequency married ( 4 ) with the accuracy of the classification of patients and non-patients respectively was 57.14% and 66.67%. Overall, the logistic regression model that has been obtained can classify respondents of 61.9%.

On Computational Bayesian Ordinal Logistic Regression Link Function in Cases of Cervical Cancer in Tuban

“…Pre-cancer result suggests that there is an abnormal change in cervical cells, while positive cancer result indicates abnormal malignant cells in cervical area. The process of cancer infection usually takes a long time, from 10-20 years [4]. To understand the influencing factors of this result, possible factors should be observed.…”

“…This result differs from that of [1]'s study which applied Maximum Likelihood Estimation and suggested that the predicting factors of cervical cancer test results are the use of contraceptives, childbirth experience, menstrual cycle, and history of miscarriage. Based on a research by [4] which uses logistic regression, the predicting factors found in Ambon are age and marriage frequency. Another study was also carried out by [35] in Afrika by applying ordinal regression with maximum likelihood method.…”

“…This disease is primarily caused by Human Papilloma Virus (HPV) [3]. The high mortality rate is resulted by late treatment, where patients only seek for help during the late stage of the disease [4]. There are approximately 52 million women in Indonesia with cancer risk, and 36% of female cancer patients suffer from cervical cancer [5].…”