IMPLEMENTATION OF RANDOM FOREST ALGORITHM TO CLASSIFY THE SEVERITY LEVEL OF BREAST CANCER

Abstract

Cancer is the most common disease every year. Many cases occur, especially in Indonesia. Breast Cancer is one of the most common types of cancer. According to Global Burden Cancer (GLOBOCAN) published in 2020, breast cancer is the most common cancer incidence, which is around 65.858 new cases in 2020. Breast cancer can be classified into two types, namely benign and malignant. Benign cancer or can be called a tumor, which has the property of not damaging the surrounding cells. This benign cancer can heal by itself. However, in some cases still require medical treatment. Malignant cancer speard and can damage the cells that are around them. Malignant cancer spreads quickly and can be fatal. In this final project, a classification web application for breast cancer is developed. The web application is called ‘Patoclass’. In this application, a Random Forest algorithm is used. Random Forest is one of many classification techniques, and it`s an algorithm for big data classification. Random Forest classification is applied to check cancer data to achieve a more accurate classification performance. The accuracy in this application is 95%.