Deteksi Dini Kanker Kulit menggunakan K-NN dan Convolutional Neural Network

Penulis

  • Teresia R. Savera Sekolah Teknik Elektro dan Informatika - ITB
  • Winsya H. Suryawan Sekolah Teknik Elektro dan Informatika ITB
  • Agung Wahyu Setiawan Sekolah Teknik Elektro dan Informatika - ITB http://orcid.org/0000-0002-7392-9190

DOI:

https://doi.org/10.25126/jtiik.2020702602

Abstrak

Kanker kulit adalah salah satu jenis kanker yang dapat menyebabkan kematian sehingga diperlukan sebuah aplikasi perangkat lunak yang dapat digunakan untuk membantu melakukan deteksi dini kanker kulit dengan mudah. Sehingga diharapkan deteksi dini kanker kulit dapat terdeteksi lebih cepat. Pada penelitian ini terdapat dua metode yang digunakan untuk melakukan deteksi dini kanker kulit yaitu deteksi dengan klasifikasi secara regresi dan artificial neural network dengan arsitektur convolutional neural network. Akurasi yang diperoleh dengan menggunakan klasifikasi secara regresi adalah sebesar 75%. Sementara, akurasi deteksi yang didapatkan dengan menggunakan convolutional neural network adalah sebesar 76%. Hasil yang diperoleh dari kedua metoda ini masih dapat ditingkatkan pada penelitian lanjutan, yaitu dengan cara melakukan prapengolahan pada set data citra yang digunakan. Sehingga set data yang digunakan memiliki tingkat pencahayaan, sudut (pengambilan), serta ukuran citra yang sama. Apabila tersedia sumber daya komputasi yang besar, akan dilakukan penambahan jumlah citra yang digunakan, baik itu sebagai set data latih maupun uji.

 

Abstract

Skin cancer is one type of cancer that can cause death for many people. Because of this, an application is needed to easily detect skin cancer early that the cancer can be handled with more quickly. In this study there were two methods used to detect skin cancer, namely detection by regression classification and detection by classifying using artificial neural networks with network convolutional architecture. Detection with regression classification gives an accuracy of 75%. While detection using convolutional neural networks gives an accuracy of 76%. These proposed early detection systems can be improved to increase the accuracy. For further development, several image processing techniques will be applied, such as contrast enhancement and color equalization. For future works, if there is more computational resource, more images can be used as dataset and implement the deep learning algorithm to improve the accuracy.


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Referensi

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Diterbitkan

18-02-2020

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Ilmu Komputer

Cara Mengutip

Deteksi Dini Kanker Kulit menggunakan K-NN dan Convolutional Neural Network. (2020). Jurnal Teknologi Informasi Dan Ilmu Komputer, 7(2), 373-378. https://doi.org/10.25126/jtiik.2020702602