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All Journal Majalah Ilmiah METHODA
Revania Juniarta Siahaan
Universitas Methodist Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Medicine & Pharmacology Public Health

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Prediksi Prognosis Kanker Payudara Menggunakan Hybrid ANN-KNN Revania Juniarta Siahaan; Margaretha Yohanna; Harlen Gilbert Simanullang
Majalah Ilmiah METHODA Vol. 16 No. 2 (2026): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol16No2.pp221-229

Abstract

Breast cancer is a disease with a high incidence and mortality rate worldwide. Determining patient prognosis is often challenging due to the complex clinical factors involved. This study aims to develop a model for predicting breast cancer prognosis using a hybrid Artificial Neural Network (ANN) and K-Nearest Neighbors (KNN) method. The dataset used is the Breast Cancer Wisconsin Prognostic (WPBC), obtained from the UCI Machine Learning Repository, comprising 198 patient data with 35 attributes. The research steps include data cleaning, label transformation, normalization using Min-MAX Scaler, feature extraction using ANN, and classification using KNN. The optimal K-value was determined by testing K=1, K=3, K=5, and K=7 using stratified K-fold cross-validation. Test results indicate that the highest accuracy of 84.62% was achieved in the fifth fold with K=7.
Co-Authors Simanullang, Harlen Gilbert Yohanna, Margaretha