PREDIKSI KEKAMBUHAN KANKER PAYUDARA DENGAN ALGORITMA C4.5

Ai Rita Rizqiah (Program Pascasarjana Magister Ilmu Komputer STMIK Nusa Mandiri)
Agus Subekti (Pusat Penelitian Elektronika dan Telekomunikasi Lembaga Ilmu Pengetahuan Indonesia (LIPI))

Techno Nusa Mandiri : Journal of Computing and Information Technology
Vol 15 No 2 (2018): Techno Nusa Mandiri : Journal of Computing and Information Technology Periode Se

Breast cancer is known as the fifth cause of death based on WHO data in 2015. The risk of developing breast cancer will increase with age, family medical history, personal medical history, caucasian descent, early menstruation, late menopause and others. This study aims to predict the use of Naïve Bayes and C4.5 data mining algorithms to classify the recurrence of cancer patients based on certain attributes in the breast cancer dataset. The data mining process will help identify the range or value of various attributes of what causes breast cancer. The results of this study indicate that the C4.5 algorithm has an accuracy value of 75.5% better than Naïve Bayes which only has an accuracy value of 72.7%.