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All Journal Journal of Engineering and Technological Sciences Mekanika: Majalah Ilmiah Mekanika Jurnal Teknik Sumber Daya Air
Mamad Tamamadin
Department Of Meteorology, Institut Teknologi Bandung, Labtek XI Building Floor 1, Jalan Ganesa 10 Bandung 40132, Indonesia
Civil Engineering, Building, Construction & Architecture Energy Engineering Environmental Science

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Development of Hydro-Meteorological Hazard Early Warning System in Indonesia Susandi, Armi; Tamamadin, Mamad; Pratama, Alvin; Faisal, Irvan; Wijaya, Aristyo R.; Pratama, Angga F.; Pandini, Olgha P.; Widiawan, Destika Agustina
Journal of Engineering and Technological Sciences Vol 50, No 4 (2018)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (841.332 KB) | DOI: 10.5614/j.eng.technol.sci.2018.50.4.2

Abstract

This paper discusses the result of the development of a hydro-meteorological hazard early warning system (H-MHEWS) that combines weather prediction from Weather Research and Forecasting (WRF) and the hydrometeorological hazard index from the National Disaster Management Authority (BNPB), Indonesia. In its current development phase, the hazards that H-MHEWS predicts are floods, landslides, and extreme weather events. Potential hazard indices are obtained by using an overlay approach and resampling so that the data have a 100-m spatial resolution. All indices are classified into 4 status categories: “No alert”, “Advisory”, “Watch”, and “Warning”. Flood potential is produced by overlaying rainfall prediction at 3-hour intervals with the flood index. Landslide potential is produced by overlaying rainfall prediction with the landslide index. Extreme weather potential is divided into 3 categories, i.e. heavy rain, strong winds, and extreme ocean waves. The whole prediction is dynamic, following weather predictions at 3-hour intervals. The hazard prediction results will trigger a ‘Warning’ alert in case of emergency status. This alert will be set up in a notification system to make it easier for the user to identify the most dangerous hydrometeorological hazard events.
Development of Hydro-Meteorological Hazard Early Warning System in Indonesia Armi Susandi; Mamad Tamamadin; Alvin Pratama; Irvan Faisal; Aristyo R. Wijaya; Angga F. Pratama; Olgha P. Pandini; Destika Agustina Widiawan
Journal of Engineering and Technological Sciences Vol. 50 No. 4 (2018)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2018.50.4.2

Abstract

This paper discusses the result of the development of a hydro-meteorological hazard early warning system (H-MHEWS) that combines weather prediction from Weather Research and Forecasting (WRF) and the hydrometeorological hazard index from the National Disaster Management Authority (BNPB), Indonesia. In its current development phase, the hazards that H-MHEWS predicts are floods, landslides, and extreme weather events. Potential hazard indices are obtained by using an overlay approach and resampling so that the data have a 100-m spatial resolution. All indices are classified into 4 status categories: "No alert", "Advisory", "Watch", and "Warning". Flood potential is produced by overlaying rainfall prediction at 3-hour intervals with the flood index. Landslide potential is produced by overlaying rainfall prediction with the landslide index. Extreme weather potential is divided into 3 categories, i.e. heavy rain, strong winds, and extreme ocean waves. The whole prediction is dynamic, following weather predictions at 3-hour intervals. The hazard prediction results will trigger a 'Warning' alert in case of emergency status. This alert will be set up in a notification system to make it easier for the user to identify the most dangerous hydrometeorological hazard events.
Penerapan Deep Learning untuk Prediksi Tinggi Muka Air Sungai dengan Mempertimbangkan Faktor Operasi Bendungan Tamamadin, Mamad; Subrata, Oky; Akrom, Isnan Fauzan
Jurnal Teknik Sumber Daya Air Vol. 5 No. 2 (Desember 2025)
Publisher : Himpunan Ahli Teknik Hidraulik Indonesia (HATHI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56860/jtsda.v5i2.150

Abstract

Indonesia is a flood-prone region, making early detection through accurate river water level prediction essential by utilizing efficient modeling methods. This study aims to develop a high-accuracy water level (TMA) prediction model at several river flow monitoring stations by employing spatial rainfall map datasets and dam discharge information as input variables in a deep learning framework that combines CNN and LSTM architectures. The model was tested under two scenarios, with and without dam operation, and its predictive performance was evaluated at three monitoring sites (Katulampa, Kampung Kalapa, and MT. Haryono). The initial evaluation using only spatial rainfall input for the MT. Haryono station showed a correlation coefficient of 0.65, MAE of 0.412 m, and NSE of 0.58. After incorporating multiple rainfall images and integrating discharge data based on dam operation scenarios, a significant improvement in prediction accuracy was observed across all stations, with the correlation increasing to 0.88, MAE decreasing to 0.137 m, and NSE rising to 0.85. These findings confirm that the inclusion of additional hydrological information, particularly dam operation data, can substantially enhance the reliability of river water level prediction models.
Analytical Review of Numerical Analysis in Hydrodynamic Performance of the Ship: Effect to Hull-Form Modifications Bahatmaka, Aldias; Fitriyana, Deni Fajar; Anis, Samsudin; Maulana, Achmad Yanuar; Tamamadin, Mamad; Lee, Sang Won; Cho, Joung Hyoung
Mekanika: Majalah Ilmiah Mekanika Vol 23, No 1 (2024): MEKANIKA: Majalah Ilmiah Mekanika
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/mekanika.v23i1.83635

Abstract

This review paper provides an overview of simulation-based hydrodynamic design optimization for ship hull forms. It also includes a numerical analysis aimed at accomplish early-stage simulation-based design in terms of hydrodynamic performance. A hydrodynamic module, a hull surface modeling module, and an optimization module are the primary components of this numerical analysis. The hydrodynamic module includes both simple design approaches and high-fidelity numeric tools; these integrated tools are used to evaluate hydrodynamic performances at different design stages. The hull surface modeling module offers a variety of techniques for ship hull surface representation and modification. It is also used to automatically create hull forms or change existing hull forms based on hydrodynamic performance and design constraints. The optimization module includes several optimization algorithms and surrogate models used to determine optimal designs in terms of hydrodynamic performance. Numerical findings indicate that the current tool is well suited for hull form design optimization at the early design stage because it can produce effective optimal designs within a short time.
Co-Authors Aldias Bahatmaka Alvin Pratama Angga F. Pratama Aristyo R. Wijaya Armi Susandi Cho, Joung Hyoung Destika Agustina Widiawan Faisal, Irvan Fitriyana, Deni Fajar Irvan Faisal Isnan Fauzan Akrom Lee, Sang Won Maulana, Achmad Yanuar Olgha P. Pandini Pandini, Olgha P. Pratama, Angga F. Samsudin Anis Subrata, Oky Susandi, Armi Widiawan, Destika Agustina Wijaya, Aristyo R.