Klasifikasi Citra Digital Mammografi Berdasarkan Luas Diameter Kanker Payudara dengan Metode K-Means Clustering - Mulyana, Dadang Iskandar; Wulandari, Anisah (Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), 2024)
Breast cancer is one of the deadly diseases with a mortality rate that increases every year because the higher the stage of cancer, the smaller the chance of people to recover. Technology is currently applied to the medical field such as MRI, CT Scan, and Mammography. Mammography can be done to identify various forms of abnormalities in the breast such as breast cancer. Therefore, in this study, the application of the K-Means method was carried out on 112 mammography digital images for classification based on the diameter area of breast cancer with the T component in the TNM system. The results of this test found that from 100% of the dataset, 24% of mammography images belonged to T2 with a diameter area between 20 mm to 50 mm, and 76% of mammography images belonged to T3-T4 with a diameter area of more than 50 mm, with an average accuracy value of 89,3028%.