Fitur Ekstraksi Gray Level Co-occurrence (GLCM) dan Histogram Pada Klasifikasi Kanker Payudara
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Simamora, Maruli Vebry
Agtriadi, Herman Bedi
Kuswandani, Dwina
Agtriadi, Herman Bedi
Kuswandani, Dwina
Subject
Teknik Informatika
Datestamp
2019-12-11 04:46:31
Abstract :
Breast Cancer is still a malignant disease and is the biggest for women both in developing countries and in the world. This application is useful for faster detection of breast cancer suffered by patients. The data used comes from Digital Images which are processed using Meotde Gray Level Co-occurrence Matrix (GLCM) and histogram to obtain a certain value. This value is used to calculate the distance of neighbors using the K-Nearest Neighbors (KNN) Method. This method uses distance to classify new objects based on learning data that is the closest distance to the new object. From this distance it can be seen that the breast cancer suffered belongs to the Benign or Malignant group
Breast Cancer is still a malignant disease and is the biggest for women both in developing countries and in the world. This application is useful for faster detection of breast cancer suffered by patients. The data used comes from Digital Images which are processed using Meotde Gray Level Co-occurrence Matrix (GLCM) and histogram to obtain a certain value. This value is used to calculate the distance of neighbors using the K-Nearest Neighbors (KNN) Method. This method uses distance to classify new objects based on learning data that is the closest distance to the new object. From this distance it can be seen that the breast cancer suffered belongs to the Benign or Malignant group
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