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All Journal CESS (Journal of Computer Engineering, System and Science) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JITK (Jurnal Ilmu Pengetahuan dan Komputer) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Technopreneur (JTech) METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Pengabdian Pada Masyarakat METHABDI Majalah Ilmiah METHODA TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Jurnal Pengabdian Masyarakat Nauli Jurnal Informatika & Teknologi Cerdas (JITC)
Yohanna, Margaretha
Universitas Methodist Indonesia
Religion Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Other

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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 Andrew Efraim Nicholas Sitompul angga prastya sianipar Dandi Daniel Siregar Darwis Robinson Manalu Dumayanti, Imelda Sri Eliza, Agnes Lasmaria Gea, Asaziduhu Imelda Sri Dumayanti indra kelana Indra Kelana Jaya Jesika Octavia Hutagaol Jeudi A. T. P. Sianturi Jimmy F. Naibaho Larosa, FGN Larosa Luhut Tony Sihotang Lumban Toruan, Desy Tri Natasia Lyna M. N. Hutapea Mario Christofell L. Tobing Marzuki Sinambela Marzuki, Sinambela Naibaho, Jimmy F. Naikson Fandier Saragih Nine Situmeang Revania Juniarta Siahaan Rumahorbo, Benget Rumapea, Yolanda Y.P. Samuel Van Basten Halomoan Manurung Saragih, Naikson F. Silaban, Cristina Adelia Putri Silalahi, Arina Prima Silalahi, Veraci Simanullang, Harlen Gilbert Sinambela Marzuki Siska Narulita Siboro Sitepu, Marheni Surianto Sitepu Surianto Sitepu Tambunan, Tio Yolanda Y. P. Rumapea Yolanda Y. P. Rumapea yolanda yulianti pratiwi rumapea