• Leonardus Sandy Ade Putra Universitas Tanjungpura
  • Eka Kusumawardhani Universitas Tanjungpura
  • Putranty Widha Nugraheni Universitas Tanjungpura
  • Lalak Tarbiyatun Nasyin Maleiva Universitas Tanjungpura
  • Vincentius Abdi Gunawan Universitas Palangka Raya



Prediksi Stroke, Klasifikasi, Kesehatan, Jaringan Syaraf Tiruan, Jaringan Perambatan Balik


Heart disease is a disease with the second-highest mortality rate in the world. This happens because of an unhealthy human lifestyle. This unhealthy lifestyle affects the performance of the body's organs in carrying out their functions. Stroke can be prevented by exercising regularly, eating nutritious foods, not consuming alcohol, and not consuming tobacco. One way to find out if someone is free from stroke or not can be done by medical check-ups. However, this method is quite expensive. Given these problems, this study aims to design an early identification system for detecting early-stage stroke. The system is designed by utilizing the condition and history of the subject for identification. This study uses a back propagation neural network for the classification process. Variations in the use of hidden layers in each experiment were used to obtain the highest accuracy in the training process. From the results of the study, it was found that the system designed can detect early stroke with an accuracy rate of 97.8%.


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