Optimalisasi Klasifikasi Kanker Payudara Menggunakan Forward Selection pada Naive Bayes

Breast cancer is a type of malignant tumor which still the number one killer where process spread or metastasis takes long time. The breast sufferers increases every year so that if detected caught early, prevention can be done early as to reduce sufferers. To risk increasing patients, it necessary do detection, several methods used assist detection such screening, computational methods. Several machine learning have been chosen solve cases prediction, especially classification algorithm, including Naive Bayes advantage being simple but having high accuracy even though they use little data. Weaknesses in Bayes, namely prediction probability result not running optimally and lack selection relevant features low. This research intended build system for detecting using method, by adding forward method feature from many exist data, because all are process. combining increase value 96.49% patients.Â