Breast Cancer Classification Using Data Mining Tool (WEKA)

Abstract

Cancer is one of the non-communicable diseases that is currently still a serious public health problem in the world. Cancer can be divided into two types, which is benign cancer and malignant cancer. Data mining has begun to be applied in various fields, one of which is in the field of health data. By exploring information or knowledge in data, it allows health facilities to improve care for cancer patients, especially breast cancer. This study focuses on classifying the type of cancer suffered by patients. The algorithms used include naïve bayes, C4.5, and support vector machine. The results of testing the three algorithms found that the support vector machine algorithm obtained the highest accuracy, which was 96.9957%.