@thesis{thesis,
		author={Luthfiyyah  Nida},
		title ={KLASIFIKASI KANKER KULIT BERDASARKAN CITRA DERMOSCOPIC MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER},
		year={2022},
		url={http://156.67.221.169/5632/},
		abstract={The design of this system is in the form of skin cancer classification using the Naïve Bayes Classifier method with the image used is dermoscopic image which is a microscope-based medical image. The process carried out is preprocessing using median filtering then feature extraction using Gray Level Co-Occurance Matrix (GLCM) with a distance of 1 and the features used are contrast, correlation, energy and homogeneity in the direction of 00, 450, 900 and 1350. The classification process is then carried out using the Naïve Bayes Classifier to identify benign skin cancer and malignant skin cancer. The test uses 200 dermoscopic-based skin cancer images which are divided into 140 training data and 60 testing data, each of which in the data is divided into benign skin cancer and malignant skin cancer. This study uses the MatLab R2018a application with accuracy testing using a confusion matrix so that the final result is 90%.}
		}