Klasifikasi Kanker Kulit Menggunakan Metode Deep Learning
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Institusion
Universitas Muhammadiyah Malang
Author
Ashari, Muhammad Rizal
Subject
T Technology (General)
Datestamp
2023-11-20 04:30:53
Abstract :
Skin is one of the important components in the human body that serves to protect the body from direct exposure to sunlight or ultraviolet. One source of vitamins for the human body is sunlight, in addition to sunlight has many benefits for the human body, but excessive sunlight can also cause cell damage to the skin, to cause skin cancer. Skin cancer is one of the diseases caused by excessive exposure to ultravioet cyanar. Skin cancer occurs and develops in the upper layers of the skin and its effects can be seen with the human eye by characterized by changes in the skin such as the appearance of lumps on the skin or shaped like tahilalat with abnormal size and shape. However, there are still many people who do not understand the symptoms or forms of this skin cancer and are often ignored. Deep learning methods are machine learning methods that are widely used today in image recognition. Now there are many studies that aim to produce a classification method that has accurate and fast results, especially in cases of skin cancer based on machine learning. The method used in this study is Deep learning using DenseNet121 model, using the amount of data as many as 3297 images. The results of the experiments that have been conducted, produce the highest accuracy sebasar 89.69% obtained from the results of training using the DenseNet121 model
Skin is one of the important components in the human body that serves to protect the body from direct exposure to sunlight or ultraviolet. One source of vitamins for the human body is sunlight, in addition to sunlight has many benefits for the human body, but excessive sunlight can also cause cell damage to the skin, to cause skin cancer. Skin cancer is one of the diseases caused by excessive exposure to ultravioet cyanar. Skin cancer occurs and develops in the upper layers of the skin and its effects can be seen with the human eye by characterized by changes in the skin such as the appearance of lumps on the skin or shaped like tahilalat with abnormal size and shape. However, there are still many people who do not understand the symptoms or forms of this skin cancer and are often ignored. Deep learning methods are machine learning methods that are widely used today in image recognition. Now there are many studies that aim to produce a classification method that has accurate and fast results, especially in cases of skin cancer based on machine learning. The method used in this study is Deep learning using DenseNet121 model, using the amount of data as many as 3297 images. The results of the experiments that have been conducted, produce the highest accuracy sebasar 89.69% obtained from the results of training using the DenseNet121 model
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