📅 03 January 2026
DOI: 10.35315/dinamik.v31i1.10328
Prediksi Aritmia pada Lansia mengunakan Linear Regression berdasarkan Data Ekg
Dinamik
Universitas Stikubank
📄 Abstract
This study aims to develop a predictive model using linear regression to identify potential arrhythmias in the elderly based on electrocardiogram (ECG) data. Data were collected through observations at healthcare facilities from elderly patients with indications of arrhythmia, then preprocessed such as cleaning, normalization, feature selection, and outlier checking were carried out. The features used include PR interval, QRS duration, QT interval, and heart rate. The dataset was divided into training data (80%) and test data (20%) to build and evaluate the model. The training results showed that the model was able to predict the risk of arrhythmia with a Mean Squared Error (MSE) value of 0.15 and a coefficient of determination (R²) close to 1. Evaluation using a confusion matrix showed an accuracy of 76.19%, precision of 82.80%, recall of 76.19%, and F1 score of 72.70%. These results prove that linear regression can be used as an initial approach in the early detection of arrhythmias non-invasively in the elderly. This study provides a foundation for the development of ECG data-based clinical decision support systems and suggests future exploration of more complex models and integration with real-time monitoring technologies.
ℹ️ Informasi Publikasi
Tanggal Publikasi
03 January 2026
Volume / Nomor / Tahun
Volume 31, Nomor 1, Tahun 2026
📝 HOW TO CITE
Sinaga, Willy; Prabowop, Agung; Siahaan, Yonathan Christian; Govandy, Govandy, "Prediksi Aritmia pada Lansia mengunakan Linear Regression berdasarkan Data Ekg," Dinamik, vol. 31, no. 1, Jan. 2026.
ACM
ACS
APA
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
Download Citation
0
Sitasi
Cek Google Scholar