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All Journal Jurnal Penelitian Rumpun Ilmu Teknik
Ary Prandika Siregar
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Computer Science & IT Engineering

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Implementasi Algoritma Random Forest Dalam Klasifikasi Diagnosis Penyakit Stroke Ary Prandika Siregar; Dwi Priyadi Purba; Jojor Putri Pasaribu; Khairul Reza Bakara
Jurnal Penelitian Rumpun Ilmu Teknik Vol. 2 No. 4 (2023): November : Jurnal Penelitian Rumpun Ilmu Teknik
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/juprit.v2i4.3039

Abstract

The most common disease in Indonesia is stroke, this disease occurs when blood flow to the brain is disrupted, either due to rupture of blood vessels or due to blockage of blood vessels. The data mining process can be a solution in identifying early symptoms of stroke. By using the Random Forest Method, it is hoped that it can be the right choice for preprocessing data in identifying early symptoms. The model results produce an adjustment of 96% of the training score and from the results table of precision, recall, F1-score, and accuracy which results in an accuracy of 0.95 or 95%, as well as the final result of AUC of 0.80 which shows that the model results are included in the good classification  
Co-Authors Dwi Priyadi Purba Jojor Putri Pasaribu Khairul Reza Bakara