Implementasi Algoritma Random Forest Dalam Klasifikasi Diagnosis Penyakit Stroke
DOI:
https://doi.org/10.55606/juprit.v2i4.3039Keywords:
Classification, Random Forest, StrokeAbstract
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
References
Jawapos.com,”Inilah Penyakit yang Paling Banyak Menyerang Masyarakat Indonesia” Jawapos.com, 2017, [Online].Available: https://www.jawapos.com/kesehatan/21/11/2017/inilah-penyakit-yang-paling-banyak-menyerang-masyarakat-indonesia/
M. A. As Sarofi, I. Irhamah, and A. Mukarromah, “Identifikasi Genre Musik dengan Menggunakan Metode Random Forest,” Jurnal Sains dan Seni ITS, vol. 9, no. 1, pp. 79–86, 2020, doi: 10.12962/j23373520.v9i1.51311.
Iskandar, N. A., Ernawati, I., & Widiastiwi, Y. (2022, August). Klasifikasi Diagnosis Penyakit Stroke Dengan Menggunakan Metode Random Forest. In Prosiding Seminar Nasional Mahasiswa Bidang Ilmu Komputer dan Aplikasinya (Vol. 3, No. 2, pp. 706-714).
Aji, P. W. S., Suprianto, S., & Dijaya, R. (2023). Prediksi Penyakit Stroke Menggunakan Metode Random Forest. Kesatria: Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen), 4(4), 916-924.
N. Permatasari, “Perbandingan Stroke Non Hemoragik dengan Gangguan Motorik Pasien Memiliki Faktor Resiko Diabetes Melitus dan Hipertensi,” Jurnal Ilmiah Kesehatan Sandi Husada, vol. 11, no. 1, 2020, doi: 10.35816/jiskh.v11i1.273.
A. Byna and M. Basit, “Penerapan Metode Adaboost Untuk Mengoptimasi Prediksi Penyakit Stroke Dengan Algoritma Naïve Bayes,” Jurnal Sisfokom (Sistem Informasi dan Komputer), vol. 9, no. 3, pp. 407–411, 2020, doi: 10.32736/sisfokom.v9i3.1023.
D. E. Cahyani, “Penerapan Machine Learning Untuk Prediksi Penyakit Stroke,” Jurnal Kajian Matematika dan Aplikasinya, vol. 3, no. January, pp. 8–14, 2022, doi: 10.17977/um055v3i1p15-22
D. Prajarini, S. Tinggi, S. Rupa, D. Desain, and V. Indonesia, “Perbandingan Algoritma Klasifikasi Data Mining Untuk Prediksi Penyakit Kulit,” Informatics Journal, vol. 1, no. 3, p. 137, 2016.
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