An artificial neural network approach for detecting skin cancer

Sugiarti Sugiarti (Universitas Muslim Indonesia)
Yuhandri Yuhandri (Universitas Putra Indonesia YPTK)
Jufriadif Na'am (Universitas Putra Indonesia YPTK)
Dolly Indra (Universitas Muslim Indonesia)
Julius Santony (Universitas Putra Indonesia YPTK)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 17, No 2: April 2019

This study aims to present diagnose of melanoma skin cancer at an early stage. It applies feature extraction method of the first order for feature extraction based on texture in order to get high degree of accuracy with method of classification using artificial neural network (ANN). The method used is training and testing phases with classification of Multilayer Perceptron (MLP) neural network. The results showed that the accuracy of test image with 4 sets of training for image not suspected of melanoma and melanoma with the lowest accuracy of 80% and the highest accuracy of 88.88%, respectively. The 4 sets of training used consisted of 23 images. Of the 23 images used as a training consisted of 6 as not suspected of melanoma images and 17 as suspected melanoma images.