Identifying Skin Cancer Disease Types With You Only Look Once (YOLO) Algorithm

Ninuk Wiliani; Anita Putri Valeria Dhiu Lusi; Nur Hikmah

doi:10.34288/jri.v5i3.241

Authors

Ninuk Wiliani Cyber University
Anita Putri Valeria Dhiu Lusi Krisnadwipayana University
Nur Hikmah Krisnadwipayana University

(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v5i3.241

Keywords:

Deep Learning, Skin, Skin Cancer, You Only Look Once (YOLO)

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 critical 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 is the model for this study because it is accurate 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 is used 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.

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