PENGUJIAN MODEL NEURAL NETWORK BERBASIS PARTICLE SWARM OPTIMIZATION UNTUK PREDIKSI PENYAKIT KANKER PAYUDARA
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.
Penulis: Achmad Udin Zailani
Kode Jurnal: jptinformatikadd140001
