ANALYSIS OF NEURAL NETWORK CLASSIFICATION ALGORITHM IN BREAST CANCER PATIENTS
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Abstract
Abstract: Breast cancer is classified as a type of malignant disease and ranks first in terms of the highest number of cancers in Indonesia and is one of the first contributors to deaths from cancer. About 43% of deaths from cancer can be prevented if breast cancer sufferers routinely carry out early detection or early diagnosis and avoid risk factors that cause cancer. In this study, a classification data mining technique will be used to predict living and deceased status using the Neural Network algorithm with rapidminer 10.0 tools. Neural network algorithm is a neural network of the human brain that is designed to follow the way the human brain processes and stores information in carrying out pattern recognition tasks, especially classification. The results of the accuracy show that the ratio of correct predictions with all data is 89.22%. With a true positive class recall of 97.08%, a true negative class recall of 49.12%, a precision Pred class. positive by 90.69% and Class precision Pred. negative by 76.71%. Analysis of positive breast cancer patients died as many as 565 records. With this classification benchmark, it is hoped that it can reduce mortality from breast cancer.
Keywords : Breast Cancer, Classification, Neural Network, Rapidminer
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