Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
S Suprianto
Universitas Muhammadiyah Sidoarjo, Sidoarjo, Indonesia
Computer Science & IT Control & Systems Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Prediksi Penyakit Stroke Menggunakan Metode Random Forest Priyo Wahyu Setiyo Aji; S Suprianto; Rohman Dijaya
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 4, No 4 (2023): Edisi Oktober
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v4i4.242

Abstract

Stroke is a medical condition classified under cerebrovascular diseases, which involve disruptions in the blood vessels of the brain. In a stroke, there is a blockage or rupture of brain blood vessels, leading to an interruption in the blood supply to specific brain regions. This can result in brain damage and symptoms related to brain functions, such as speech impairments, movements, and other functions. Nowadays, technology is advancing rapidly, greatly benefiting the medical community. One example is the development of artificial intelligence-powered programs for stroke detection. In this research, data was sourced from Kaggle.com, and the researchers utilized the random forest machine learning method. Random Forest combines independent decision trees originating from the same distribution, where the final prediction outcome is determined through a voting process. This research involved several stages, including preprocessing, processing, and evaluation. The research yielded an accuracy of 99%.
Co-Authors Priyo Wahyu Setiyo Aji Rohman Dijaya