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Breast cancer is one of the non-communicable diseases that tends to increase every year. This disease occurs almost entirely in women but can also occur in men. The best way to identify the presence of breast cancer at an early stage is to interpret an X-ray mammogram that can show abnormalities or abnormalities in the breast in a very small form. Visual identification requires vision and knowledge skills to classify results from mammogram images. Based on this, this research proposes the identification / classification of breast cancer in visual mammogram image into computer by using k-slice segmentation method, feature extraction of Gray Level Co-Occurence Matrix (GLCM) and Support Vector Machine (SVM) classification method. Applications in this study can classify / recognize the image of a normal and abnormal mammogram with a value of accuracy obtained by 80%.

Klasifikasi Citra Mammogram Menggunakan Metode K-Means, GLCM, dan Support Vector Machine (SVM)