Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Vol 2 No 8 (2018): Agustus 2018

Klasifikasi Risiko Hipertensi Menggunakan Metode Learning Vector Quantization (LVQ)

Ivan Agustinus (Fakultas Ilmu Komputer, Universitas Brawijaya)
Edy Santoso (Fakultas Ilmu Komputer, Universitas Brawijaya)
Bayu Rahayudi (Fakultas Ilmu Komputer, Universitas Brawijaya)



Article Info

Publish Date
22 Sep 2017

Abstract

Hypertension is one of the health problems globally and perceived by the world community. From various surveys conducted, the number of cases of hypertension that occur each year will continue to grow and the number of deaths caused by hypertension also increases. This study attempts to classify hypertensive diseases. In this study using patient data of hypertension disease by divided into 4 classes. Classification method used in this research is Learning Vector Quantization. Data in the form of weight will be entered into the database system for further classification process with LVQ. Weight obtained from medical records of hypertensive patients, This study uses 12 features. This study used 6 test scenarios that resulted in recommendation of value of learning rate 0.1, multiplier learning rate 0.2, training data as much as 50%, alpha minimum 0.001, maximum iteration of 6 and train data used in the sequence of initial id. The result of accuracy obtained is 93.841%

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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 ...