Aplikasi Diagnosis Penyakit Kanker Payudara Menggunakan Algoritma Sequential Minimal Optimization - Agung Wibowo (Department of Computer Engineering, Engineering Faculty, Universitas Diponegoro, 2017)
Various methods for the diagnosis of breast cancer exist, but not many have been implemented as an application. This study aims to develop an application using SMO algorithm assisted by Weka to diagnose breast cancer. The application was web-based application and developed using Javascript. Test dataset and model formation used original Breast Cancer Database (WBCD) data without missing value. Test mode used 10-fold cross-validation. This application can diagnose breast cancer with an accuracy of 97.3645% and has a significant increase in accuracy for the diagnosis of malignant cancer.