@thesis{thesis,
		author={Agtriadi  herman bedi and Alfiani A  Wini and Kuswardani  Dwina},
		title ={KLASIFIKASI K-NEAREST NEIGHBOR CITRA  MAMMOGRAM KANKER PAYUDARA MENGGUNAKAN  FITUR EKSTRAKSI GRAY LEVEL CO-OCCURANCE MATRIX},
		year={2023},
		url={http://156.67.221.169/5657/},
		abstract={Breast cancer is a maglignant tumor that attacks breast. Based on the results of Globocan
Observatory 2020 data, breast cancer cases in Indonesia ranked first, with total new 
cases in 2018 amounting to 58,256 (16.7%) cases, in female patients infected with breast 
cancer amounting to 58,256 (30.9%) cases while for breast cancer death cases became 
second with a total of 22,692 (11.0%). Using the K- Nearest Neighbor (KNN) method 
which aims to classify mammogram images, the feature extraction used is the Gray Level 
Co-Occurrence Matrix (GLCM). The implementation is carried out as a learning on the 
K- Nearest Neighbor (KNN) and Gray Level Co-Occurrence Matrix (GLCM) methods.
From the research that has been carried out, 20 data will be used to be tested on the K?Nearest Neighbor classification to get test results on the mammogram image 
classification system that has been made using the Confusion Matrix with an accuracy of 
80%.}
		}