Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 6 No 5 (2022): Mei 2022

Klasifikasi Risiko Penyakit pada Ibu Hamil menggunakan Metode Modified K-Nearest Neighbor (MKNN)

Yogi Pinanda (Fakultas Ilmu Komputer, Universitas Brawijaya)
Wayan Firdaus Mahmudy (Fakultas Ilmu Komputer, Universitas Brawijaya)
Edy Santoso (Fakultas Ilmu Komputer, Universitas Brawijaya)



Article Info

Publish Date
04 Mar 2022

Abstract

Pregnant women need to increase their knowledge to find out how big the level of risk of getting a disease, especially because of the vulnerability of pregnant women. Classification of the level of disease risk in pregnant women is expected to assist users in finding the right solution to overcome it. The classification method used to determine the level of disease risk for pregnant women uses Modified K-Nearest Neighbor (MKNN). Classification of disease risk levels in pregnant women using the Modified K-Nearest Neighbor (MKNN) method can make it easier to detect disease based on existing factors. The Modified K-Nearest Neighbor (MKNN) method is implemented on the expert system inference engine so that conclusions can be drawn based on existing knowledge. The results of the accuracy of the system obtained after testing is 85% which indicates that the Modified K¬-Nearest Neighbor (MKNN) method is suitable for studying the level of disease risk in pregnant women.

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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 ...