Implementation of Naive Bayes Method in Classification of Breast Cancer Disease - Alamsyah; Eko Prasetyo; R Dimas Prasetyo (Fakultas Teknik Universitas Bhayangkara, 2017)
Less knowledge of early symptoms of breast cancer and how to deal with it early and the number of specialist doctorswho are still limited is one factor contributors because of the increasing number of people affected by breast cancerdisease. The development of breast cancer disease classification system aims to predict the early diagnosis of breastcancer disease in users or patients into two categories of malignant or benign. The initial diagnoses of this systemprediction 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 Usingthe naive bayes method to process diagnostic data in patients, the results of this system test show that the system isable to predict and classify breast cancer disease into two categories (malignant or benign) with the amount of datatesting of 500 data. With the output of malignant or YA and benign or NO, the system is able to predict with an accuracyvalue of 98%.