Short-horizon forecasting of near-surface methane (CH?) in tropical urban environments remains underexplored. This study compares Long Short-Term Memory (LSTM) and Transformer-based models for three-hour-ahead surface CH? forecasting in Jakarta using CAMS EAC4 reanalysis and BMKG Kemayoran observations. Historical CH?,...
Farid Faisal, Choirul Basir, A. A. Waskita· Jurnal Informatika, Teknolog...· 0 citations
Results show that model selection should consider spatial, temporal, and physical diagnostics alongside global accuracy metrics alongside global accuracy metrics in very short-range forecasting of 850-hPa winds over tropical urban-coastal regions.
Gatot Andriyanto, A. Susanto, A. A. Waskita· Jurnal Informatika, Teknolog...· 0 citations
Findings show that rigorous parameter selection, bias correction, and multi-run validation, not architectural complexity alone, make decomposition-based deep learning reliable for PM2.5 prediction, offering a reproducibility-aware baseline for a future Jakarta air-quality early-warning system.
Dwi Yuwono, A. A. Waskita, Tukiyat Tukiyat· JOURNAL OF APPLIED INFORMATI...· 0 citations
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