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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Aldy Satria
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Jenis Kanker Berdasarkan Struktur Protein Menggunakan Metode Neighbor Weighted K-Nearest Neighbor (NWKNN) Aldy Satria; Marji Marji; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 4 (2019): April 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Cancer is non-infectious disease with large population in the world. Cancer is ranked on 7th deadliest disease in Indonesia. Mostly cancer happened because of gene mutation that cause changes in protein form,one of them happens in protein 53 (p53). Mutation of gene p53 most commonly found in human cancers. From this case required a system that can classify the types of cancer. One of methods used is Neighbor Weighted K-Nearest Neighbor (NWKNN). Data used in this paper consists of 752 protein sequences data with 393 sequence length. Classification class includes non-cancer, breast cancer, collorectal cancer and lung cancer. NWKNN is improvement of K-Nearest Neighbor (KNN) method with addition of weight class in its classification class scoring calculation. The test is conducted by dividing dataset into training data and testing data with training data and testing data ratio 80%:20%, 70%:30%, 60%:40, 50%:50, 40%:60%, 30%:70%, 20%:80%, 10%:90% from dataset. The result shows that 80%:20% ratio with K=8 and E=3 provided the highest accuracy eate of 80.666%.
Co-Authors Dian Eka Ratnawati Marji Marji