Implementation of Naive Bayes Method in Classification of Breast Cancer Disease

Abstract

Less knowledge of early symptoms of breast cancer and how to deal with it early and the number of specialist doctors
who are still limited is one factor contributors because of the increasing number of people affected by breast cancer
disease. The development of breast cancer disease classification system aims to predict the early diagnosis of breast
cancer disease in users or patients into two categories of malignant or benign. The initial diagnoses of this system
prediction variable include Clump Thickness, Uniformity of Cell Size, Uniformity of Cell Shape, Marginal Adhesion,
Single Epithelial Cell Size (Single Epithelial Cell) Size), Bare nuclei, Bland Chromatin, Normal nucleoli, Mitosis Using
the naive bayes method to process diagnostic data in patients, the results of this system test show that the system is
able to predict and classify breast cancer disease into two categories (malignant or benign) with the amount of data
testing of 500 data. With the output of malignant or YA and benign or NO, the system is able to predict with an accuracy
value of 98%.