Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 2 No 9 (2018): September 2018

Identifikasi Penyakit Gagal Ginjal Menggunakan Metode Neighbor Weighted K-Nearest Neighbor (NWKNN)

Azizul Hanifah Hadi (Fakultas Ilmu Komputer, Universitas Brawijaya)
Dian Eka Ratnawati (Fakultas Ilmu Komputer, Universitas Brawijaya)
Candra Dewi (Fakultas Ilmu Komputer, Universitas Brawijaya)



Article Info

Publish Date
09 Feb 2018

Abstract

Kidney disease can be caused by several factors such as hypertension, uric acid levels, creatinine levels, diabetes, and many others. From that factors, we know about the level of kidney disease risk. Some people are unaware, lazy and indifferent about health, especially on kidney disease because of the long process and complicated. According to the Indonesian Renal Registry, in 2014 patients with kidney disease in Indonesia reach 12,770 inhabitants. Therefore, we need a system that can detect or identify the kidney disease. In this research, we will identify the kidney disease using Neighbor Weighted K-Nearest Neighbor (NWKNN) method. This method is similar to the KNN method but the differentiates are in the weighting process in each identification class. Identification class in this study decided in two part, ckd or exposed to kidney disease and notckd or not affected kidney disease. The results of this study indicate that the NWKNN method can identify kidney disease when the data are 150 data and the test data are 50 data with K = 2 and E = 2 and accuracy level is 88%.

Copyrights © 2018






Journal Info

Abbrev

j-ptiik

Publisher

Subject

Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Description

Jurnal Pengembangan Teknlogi Informasi dan Ilmu Komputer (J-PTIIK) Universitas Brawijaya merupakan jurnal keilmuan dibidang komputer yang memuat tulisan ilmiah hasil dari penelitian mahasiswa-mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya. Jurnal ini diharapkan dapat mengembangkan penelitian ...