Estimasi Persentase Lemak Tubuh Berdasarkan Variabel Berat dan Tinggi Badan dengan Pendekatan Regresi Linear Berganda

Abstrak

Body fat percentage is an important indicator in determining a person's health status. This study aims to analyze the effect of body weight and height on body fat percentage using multiple linear regression methods with the help of Orange Data Mining. The data used was obtained from (https://www.kaggle.com/datasets/fedesoriano/body-fat-prediction-dataset), with a total of 100 samples.The analysis was carried out with multiple linear regression tests to determine the relationship between the independent variables (X1 and X2) on the dependent variable (Y). Data processing and visualization of regression models were carried out using Orange Data Mining, an open-source software that simplifies data analysis without the need for complex programming. Based on the results of hypothesis testing, body weight has a more dominant positive influence than height on body fat percentage. The conclusion of this study indicates that the combination of body weight and height can be used to estimate a person's body fat percentage. The implementation of Orange Data Mining in this research is proven to simplify the regression analysis process and provide a more intuitive visualization. The results of this study are expected to be a reference in the health sector, especially in monitoring body composition and weight management.