Prediksi Jumlah Titik Ruang Terbuka Hijau (RTH) Menggunakan Metode Regresi Linier dan Model Random Forest
DOI:
https://doi.org/10.36050/d81adt50Keywords:
Data Science, Ekoregion Sumatera, Evaluasi Model, Random Forest, Regresi Linier, Prediksi, Ruang Terbuka HijauAbstract
The development and preservation of Green Open Space (GOS) is an important part of
maintaining environmental balance, especially in the Sumatra Ecoregion. This study aims to predict the
number of GOS points using a linear regression approach and the Random Forest algorithm. The data
used include variables such as area and forest area from several provinces in Sumatra. Model
performance evaluation was carried out using MAE, RMSE, and coefficient of determination (R²) metrics.
The analysis results show that the Random Forest model has superior performance compared to linear
regression, with an MAE value of 5.52, RMSE of 5.88, and R² of 0.74. Meanwhile, linear regression was
only able to achieve an R² of 0.45. These findings indicate that Random Forest is more effective in
capturing non-linear data patterns and more accurate in predicting the number of GOS points. This study
contributes to the use of data science technology to support sustainable environmental planning, as well as
becoming a basis for data-based spatial planning policy making
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