PREDIKSI HARGA RUMAH DENGAN METODE REGRESI LINEAR DAN SUPPORT VECTOR REGRESSION DI DAERAH TEBET JAKARTA SELATAN
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Abstract
Home is a basic necessity for every individual, yet the unpredictability of house prices poses a challenge in the home buying process. This research aims to predict house prices in the Tebet area, South Jakarta, using two regression algorithm models, namely Linear Regression and Support Vector Regression (SVR). The research findings indicate that the Linear Regression model outperforms the SVR model in predicting house prices with lower performance evaluation scores. Performance evaluation is conducted through Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R2 Score demonstrating that the Linear Regression model performs better in the context of the dataset used. This study provides a better understanding of the dynamics of the property market in the area and assists individuals in making smarter decisions regarding home investment.
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