Klasifikasi Penyakit Kanker Kulit Menggunakan Metode Convolutional Neural Network (Studi Kasus : Melanoma)

Reynaldi, Rio Saputro (2021) Klasifikasi Penyakit Kanker Kulit Menggunakan Metode Convolutional Neural Network (Studi Kasus : Melanoma). Undergraduate Thesis thesis, Institut Teknologi Telkom Purwokerto.

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Abstract

Skin cancer is one of the most commonly diagnosed cancers worldwide. One of the most dangerous skin diseases is melanoma cancer. Melanoma is a skin cancer that can develop in melanocytes, the skin pigment cells that produce melanin. Melanin is what absorbs ultraviolet rays and protects the skin from damage. Melanoma is a type of skin cancer that is rare and very dangerous, many lay people have not been able to distinguish between ordinary moles and melanoma. This study was conducted to classify melanoma skin cancer using the CNN method, where CNN was able to classify melanoma images. In CNN itself there is an architectural model, while the architecture used in this research is using conv2d layer, max pooling, flatten, dense, dropout, and using ReLu activation. In a previous study entitled "Classification of Pneumonia Diseases Using the Convolutional Neural Network Method with Adaptive Momentum Optimization" using 100 epochs and obtaining testing results of 78%, while in this study 50 epochs were used with an image size of 128x128, the results of the testing were obtained. by 92.64%. It is hoped that this research can help the public in distinguishing between melanoma and non-melanoma. Keywords: Skin Cancer, Melanoma, CNN

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