KLASIFIKASI JENIS PENYAKIT KANKER PAYUDARA BENIGN DAN MALIGNANT DENGAN METODE JARINGAN SYARAF TIRUAN LEARNING VECTOR QUANTIZATION; CLASSIFICATION OF DISEASES BREAST CANCER BENIGN AND MALIGNANT BY ARTIFICIAL NEURAL NETWORK LEARNING VECTOR QUANTIZATION METHOD

Nurdiyanto, Agung, Anifuddin Azis

2015 | Skripsi | FMIPA

Cancer is a broad term for a class of diseases characterized by abnormal cells that grow and invade healthy cells in the body. Breast cancer starts in the cells of the breast as a group of cancer cells that can then invade surrounding tissues or spread (metastasize) to other areas of the body. Breast cancer is a disease in which malignant (cancer) cells form in the tissues of the breast. The damaged cells can invade surrounding tissue, but with early detection and treatment, most people continue a normal life. There are two types of breast cancer tumors: those that are non-cancerous, or ‘benign’, and those that are cancerous, which are ‘malignant’. Learning vector quantization is a method to learning or training in supervised competitive layer. A competitive layer automatically learns to classify input vectors. Class obtained as a result of competitive layer only depends on the distance between vectors input. Testing the system in this research can be done classification of types breast cancer between benign and malignant. Result of the evaluation Accuracy Score classification of types breast cancer dataset Winconsin Diagnostic Breast Cancer by 98.6% on the data process 4 with parameter error maximum by 0.001, learning rate by 0.1 and decrease rate by 0.3.

Kata Kunci : classification; breast cancer; artificial neural networks; learning vector quantization