Prediksi Tekanan Darah Berdasarkan Faktor Umur dan BMI dengan Regresi Linear Berganda
Keywords:
Multiple Linear Regression, Blood Pressure, Age, Body Mass Index, PredictionAbstract
Blood pressure is a vital health metric affected by multiple factors, such as age and Body Mass Index (BMI). This research seeks to forecast blood pressure utilizing age and BMI through the multiple linear regression technique. The dataset comprises 74 samples, processed with SPSS software to develop the predictive model. The study yielded the regression equation Y = 106.635 + 0.076X₁ + 0.069X₂, with X₁ denoting age and X₂ indicating BMI. The coefficient of determination (R²) of 0.229 signifies that the model accounts for only 22.9% of the variability in blood pressure, with the remaining proportion affected by extraneous factors not addressed in this study. According to the derived model, a 27-year-old individual with a BMI of 75 is anticipated to have a blood pressure of 113.86 mmHg. The results indicate that while age and BMI affect blood pressure, other variables like food, physical activity, stress, and medical history must be taken into account to enhance predictive precision. Consequently, additional study with more sophisticated models is advised to yield more precise and representative outcomes
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