PREDIKSI PENYAKIT JANTUNG MENGGUNAKAN ALGORITMA MULTIPLE LINEAR REGRESSION
HEART DISEASE PREDICTION USING THE MULTIPLE LINEAR REGRESSION ALGORITHM
Kata Kunci:
Heart disease, multiple linear regression, risk prediction, machine learning, UCI dataset, early detection, health risk factors.Abstrak
This research, titled "Heart Disease Classification Using Multiple Linear Regression Algorithm," aims to develop an effective predictive model for detecting the risk of heart disease. Coronary heart disease is one of the leading causes of death worldwide, making early detection crucial. The multiple linear regression method was chosen for its simplicity in modeling the relationship between independent and dependent variables. The dataset used is sourced from the UCI Machine Learning Repository, which includes demographic information and health risk factors. The findings indicate that the developed model achieves an accuracy of 80.33% with high sensitivity, although it faces challenges in terms of generalization to external data. This research is expected to contribute to the development of early detection tools for heart disease.
