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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JURTEKSI PROFICIO: Jurnal Pengabdian Masyarakat Academic Journal of Computer Science Research (AJCSR) SOROT: Jurnal Pengabdian Kepada Masyarakat Computer Journal
Muttaqin, Widang
Universitas Telkom
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Mechanical Engineering Social Sciences Other

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Penerapan Ensemble Machine Learning Random Forest dan XGBoost dengan Explainable Artificial Intelligence (XAI) untuk Prediksi Urban Heat Island dan Land Surface Temperature di DKI Jakarta Hertanto Suryoprayogo; Widang Muttaqin; Annisa Desianty
Computer Journal Vol. 4 No. 2 (2026): August
Publisher : Yayasan Pendidikan Mitra Mandiri Aceh (YPMMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58477/cj.v4i2.501

Abstract

The Urban Heat Island (UHI) effect in tropical urban settings arises from interactions among built surfaces, vegetation, water bodies, and urban energy dynamics. This study modeled Land Surface Temperature (LST) in DKI Jakarta using Random Forest and XGBoost optimized with RandomizedSearchCV and 5-fold cross-validation. The analysis used 5,821 grid points at approximately 300 m resolution and five predictors: road density, NDVI, NDBI, NDWI, and distance to green open space. XGBoost slightly outperformed Random Forest, achieving R² = 0.507 and RMSE = 1.830°C compared with R² = 0.497 and RMSE = 1.849°C, although the difference was not statistically significant (Wilcoxon, p = 0.352). The RF-XGBoost ensemble did not improve performance due to very high residual correlation (r = 0.988) and a theoretical ensemble standard deviation reduction of only ~0.3%. SHAP analysis identified NDBI as the dominant predictor (mean|SHAP| = 0.986), with the strongest interaction between NDBI and road density (0.101). Hyperparameter tuning changed model ranking, statistical significance, and the leading SHAP interaction pair.
Co-Authors Achmad Udin Zailani Achmad Udin Zailani Ade Rahmat Iskandar Adelia Chitra Sazkia Ananda Alif Raditya Annisa Desianty Annisa Desianty Arif Rahman Hakim Aurellia Fira Artanti Daniswara Rafi Pandora Daniswara Rafi Pandora Deki Satria Deny Haryadi Desi Nurnaningsih Dewi Marini Umi Atmaja Fahmi Fahmi Gading Ainunzaky Widianto Haddad Alwi Yafie Haddad Alwi Yafie Hendrawan, Fadhil Rozi Hertanto Suryoprayogo Khansa Farah Fitriani Maya Silvi Lydia Muhammad Aziz Kurniawan Muhammad Rafi Ramzi Muhammad Raihan Fadani Muhammad Sheva Atallah Daffansyah Muhammad Solehuddin Nabil Marsya Azzahra Nurmaningsih, Desi Ramadhan, Yumna Zahran Sherly Nur Sausanindra Yudiansyah Yumna Zahran Ramadhan Zuki Pristiantoro Putro