Identifying Skin Cancer Disease Types With You Only Look Once (YOLO) Algorithm
Abstract
The skin is the outermost vital organ and is susceptible to various diseases, including skin cancer. The number of cases of skin cancer around the world continues to increase every year, including in Indonesia. Proper handling is very important to cure skin cancer, and one of the solutions that can be used is the Deep Learning method. This study aims to apply the Deep Learning method, specifically an object detection algorithm called You Only Look Once (YOLO), for early skin cancer detection. The YOLOv5s algorithm was chosen as the model for this study because it has good accuracy and can detect objects in real-time. The research method involved collecting data on skin cancer cases and training the YOLOv5s model. After training, model testing was carried out to evaluate the ability to detect skin cancer. The test results show that the YOLOv5s model has an accuracy of 89.1% in detecting skin cancer types. This research has important implications in the health sector, especially in early skin cancer detection.
Downloads
References
Agustina, Feri. 2022. “Deteksi Kematangan Buah Pepaya Menggunakan Algoritma YOLO Berbasis Android.” Jurnal Ilmiah Infokam 18(2):70–78. doi: 10.53845/infokam.v18i2.320.
Ahmad, Tanvir, Yinglong Ma, Muhammad Yahya, Belal Ahmad, Shah Nazir, Amin Ul Haq, and Rahman Ali. 2020. “Object Detection through Modified YOLO Neural Network.” Scientific Programming 2020:1–10. doi: 10.1155/2020/8403262.
Akhyar, Fityanul, Ledya Novamizanti, and Tita Riantiarni. 2022. “Sistem Inspeksi Cacat Pada Permukaan Kayu Menggunakan Model Deteksi Obyek YOLOv5.” ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 10(4):990. doi: 10.26760/elkomika.v10i4.990.
Aningtiyas, Prisky Ratna, Agus Sumin, and Setia Wirawan. 2020. “Pembuatan Aplikasi Deteksi Objek Menggunakan TensorFlow Object Detection API Dengan Memanfaatkan SSD MobileNet V2 Sebagai Model Pra - Terlatih.” Jurnal Ilmiah Komputasi 19(3):421–30. doi: 10.32409/jikstik.19.3.68.
Dio, Muhamad, Riza Pratama, Bayu Priyatna, Shofa Shofiah, and April Lia. 2022. “Deteksi Objek Kecelakaan Pada Kendaraan Roda Empat Menggunakan Algoritma YOLOv5 Car Vehicle Accident Object Detection Using YOLOv5 Algorithm.” 12(2):15–24.
Ieamsaard, Jirarat, Surapon Nathanael Charoensook, and Suchart Yammen. 2021. “Deep Learning-Based Face Mask Detection Using YoloV5.” Proceeding of the 2021 9th International Electrical Engineering Congress, IEECON 2021 428–31. doi: 10.1109/iEECON51072.2021.9440346.
Kanwal, Neel, Roger Amundsen, Helga Hardardottir, Emiel A. M. Janssen, and Kjersti Engan. 2023. “Detection and Localization of Melanoma Skin Cancer in Histopathological Whole Slide Images.”
Kumar, Ayushi, and Avimanyou Vatsa. 2022. “Untangling Classification Methods for Melanoma Skin Cancer.” Frontiers in Big Data 5(March):1–11. doi: 10.3389/fdata.2022.848614.
Luqman Hakim, Zamah Sari, and Handhajani Handhajani. 2021. “Klasifikasi Citra Pigmen Kanker Kulit Menggunakan Convolutional Neural Network.” Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi) 5(2):379–85. doi: 10.29207/resti.v5i2.3001.
Lusiana, Lusiana, Ari Wibowo, and Kartika Dewi. 2023. “Implementasi Algoritma Deep Learning You Only Look Once ( YOLOv5 ) Untuk Deteksi Buah Segar Dan Busuk.” 11(1):123–30.
Mulyana, Dadang iskandar, and M. Ainur Rofik. 2022. “Implementasi Deteksi Real Time Klasifikasi Jenis Kendaraan Di Indonesia Menggunakan Metode YOLOV5.” 6:13971–82.
Schierbeck, Juliane, Tine Vestergaard, and Anette Bygum. 2019. “Skin Cancer Associated Genodermatoses: A Literature Review.” Acta Dermato-Venereologica 99(4):360–69. doi: 10.2340/00015555-3123.
Septyanto, Bangga Adi, Suryo Adhi Wibowo, and Casi Setianingsih. 2022. “Implementasi Face Recognition Berbasis Deep Neural Network Sebagai Sistem Kendali Pada Quadcopter.” E-Proceeding of Engineering 8(6):3036–50.
Setiabudi, Jordaniel, Made Wardhana, I. Gusti Ayu Agung Elis Indira, and Ni Made Dwi Puspawati. 2021. “Profil Pra Kanker Dan Kanker Kulit RSUP Sanglah Periode 2015 - 2018.” Jurnal Medika Udayana 10(3):83–89.
Sofia Saidah, I. Putu Yowan Nugraha Suparta, and Efri Suhartono. 2022. “Modifikasi Convolutional Neural Network Arsitektur GoogLeNet Dengan Dull Razor Filtering Untuk Klasifikasi Kanker Kulit.” Jurnal Nasional Teknik Elektro Dan Teknologi Informasi 11(2):148–53. doi:10.22146/jnteti.v11i2.2739.
Abstract viewed = 40 times
PDF downloaded = 22 times
Copyright (c) 2023 Ninuk Wiliani, Nur Hikmah, Anita Putri Valeria
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
An author who publishes in the Jurnal Riset Informatika agrees to the following terms:
- The author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-NonCommercial 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal
- The author is permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work (See The Effect of Open Access).
Read more about the Creative Commons Attribution-NonCommercial 4.0 Licence here: https://creativecommons.org/licenses/by-nc/4.0/.
2.png){kind=logo}
