Algoritma Neural Network Menggunakan Model Particle Swarm Optimization Untuk Prediksi Penyakit Kanker Payudara

Abstract

ABSTRACT

Breast cancer is one of the causes of cancer deaths in women worldwide. One technique to diagnose breast cancer: mammography. In this study developed a system to classify the "Breast Cancer" using Backpropagation neural network optimized with Particle Swarm Optimization for classifying tumors of the symptoms that cause breast cancer. The main objective of this study was to develop a more cost effective and easy to use system to support doctors. For the problem of diagnosis of breast cancer tumor symptoms, the experimental results show that the neural network based model of particle swarm optimization achieved a high degree of accuracy. Dataset used in this study were breast cancer database from the University of Wisconsin Machine Learning (UCI) Repository.

 

Keywords: Breast Cancer, Backpropagation, Particle Swarm Optimization, Accuracy