The Pengembangan Model Prediktif untuk Penyakit Jantung Menggunakan Teknik Data Mining: Abastrak, Pendahuluan, Landasan Teori, Metode Penelitian, Hasil dan Pembahasaan, Kesimpulan, Ucapan Terimakasih, Referensi - Pringgandani, Rizal (Jurnal SIGMA, 2024)
Throughout the world, heart disease is still a health problem. To study the development of a predictive model using the Decision Tree algorithm, clinical data from patients with a history of heart disease was collected and analyzed. The decision tree model achieved an accuracy of 80.88%, indicating the ability to correctly predict the target category in the majority of cases. These results suggest that there is potential for earlier intervention and prevention. Additional evaluation is needed to understand the components that influence the results and improve model performance. This research helps improve heart disease predictions using data mining techniques.