MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer
Vol 21 No 3 (2022)

Stroke Prediction Using Machine Learning Method with Extreme Gradient Boosting Algorithm

Abd Mizwar A Rahim (Universitas Amikom Yogyakarta)
Andi Sunyoto (Universitas Amikom Yogyakarta)
Muhammad Rudyanto Arief (Universitas Amikom Yogyakarta)



Article Info

Publish Date
23 Jul 2022

Abstract

Based on data obtained from WHO, stroke is a disease that ranks as the second most deadly disease. The cause of a stroke is when a blood vessel is hit or ruptured, resulting in a part of the brain not getting the blood supply that carries the oxygen it needs, leading to death. By utilizing technology in the health sciences, especially in the health sector, machine learning models can adjust and make it easier for users to predict certain diseases. Previous studies have had problems with low accuracy when used in healthcare. The purpose of this research is to increase accuracy by proposing the application of one of the ensemble learning algorithms, namely the Xtreme Gradient Boosting algorithm. This stroke prediction research uses the Xtreme Gradient Boosting Algorithm; the application of this method with split data Training data and 70/30 test data, 70% of the training data is 3582, 30% of the test data is 1536, and the results are 96% accuracy with these results having good results. This study increase accuracy in predicting stroke cases and get better accuracy than previous studies.

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Journal Info

Abbrev

matrik

Publisher

Subject

Computer Science & IT

Description

MATRIK adalah salah satu Jurnal Ilmiah yang terdapat di Universitas Bumigora Mataram (eks STMIK Bumigora Mataram) yang dikelola dibawah Lembaga Penelitian dan Pengabadian kepada Masyarakat (LPPM). Jurnal ini bertujuan untuk memberikan wadah atau sarana publikasi bagi para dosen, peneliti dan ...