Prediksi Penyakit Stroke Menggunakan Metode Random Forest

Priyo Wahyu Setiyo Aji(1*), S Suprianto(2), Rohman Dijaya(3),

(1) Universitas Muhammadiyah Sidoarjo, Sidoarjo, Indonesia
(2) Universitas Muhammadiyah Sidoarjo, Sidoarjo, Indonesia
(3) Universitas Muhammadiyah Sidoarjo, Sidoarjo, Indonesia
(*) Corresponding Author

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%.

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References


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DOI: https://doi.org/10.30645/kesatria.v4i4.242

DOI (PDF): https://doi.org/10.30645/kesatria.v4i4.242.g240

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