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Open Access Aplikasi Diagnosis Penyakit Kanker Payudara Menggunakan Algoritma Sequential Minimal Optimization

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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. Beragam metode untuk diagnosis kanker payudara, namun belum banyak yang diimplementasikan menjadi sebuah aplikasi. Penelitian ini bertujuan untuk mengembangkan aplikasi berdasarkan model hasil kalkulasi algoritma SMO berbantuan Weka untuk mendiagnosis penyakit kanker payudara. Aplikasi dikembangkan berbasis web menggunakan Javascript. Dataset pengujian dan pembentukan model menggunakan data Winconsin Breast Cancer Database original (WBCD) tanpa nilai hilang. Mode pengujian menggunakan 10-fold cross validation. Aplikasi ini dapat mendiagnosis kanker payudara dengan akurasi 97.3645% dan memiliki peningkatan akurasi yang signifikan untuk diagnosis kanker ganas.
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Document Type: Research Article

Affiliations: Program Studi Teknik Informatika, STMIK Nusa Mandiri Sukabumi

Publication date: January 1, 2017

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