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All Journal Jurnal Pengembangan Energi Nuklir Majalah Geografi Indonesia Geo-Image Journal JLBG (Jurnal Lingkungan dan Bencana Geologi) (Journal of Environment and Geological Hazards) JURNAL ILMIAH GEOMATIKA MAJALAH ILMIAH GLOBE Jambura Geoscience Review IJEEM - Indonesian Journal of Environmental Education and Management Journal of Applied Geology Environmental and Materials
Tito Latif Indra
Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Indonesia, Depok
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Physics Social Sciences

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Flood Disaster Prediction Model Using Long Short-Term Memory (LSTM) in Pekalongan, Central Java. Asrofi, Muhammad; Septyandy, Muhammad Rizqy; Indra, Tito Latif
Journal of Applied Geology Vol 8, No 2 (2023)
Publisher : Geological Engineering Department Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jag.92417

Abstract

Pekalongan is located in the northern part of Java Island, directly adjacent to the sea in the north. Natural disasters that often occur in Pekalongan are floods, especially in the north of the area, which has a height of 0 meters above sea level. In addition, Pekalongan also has a relatively low land slope of around 0 – 5%, which makes it challenging to distribute water and construct drainage. This study aims to be able to perform predictive modeling of flood-prone areas for the next five years. This study used eight parameters: rainfall, elevation, slope, distance to the river, distance to the sea, groundwater table to surface, soil type, and land use. This research used the Long Short-Term Memory (LSTM) method to predict rainfall parameters using the Python programming language with Jupyter Notebook software. Later, the data will be used as training and test data. Training data testing and tests are conducted to find the minimum failure or error value. The weight scoring method is carried out on each parameter to indicate areas with a high flood vulnerability level. The results showed that Pekalongan has a medium to very high vulnerability level, with a dominant high vulnerability level. The very high level of vulnerability is prevalent in the northern part of the research area, which is directly adjacent to the sea or in the North Pekalongan District. Floods that occur in the northern part of the study area are not only due to high levels of rainfall but can also occur due to the inflow of seawater towards the mainland resulting from high tides and high sea waves. The southern region of the study area has a smaller vulnerability level than the northern region, which has a medium to high vulnerability level.Keywords: Flood ∙ Hazard ∙ Precipitation ∙ LSTM ∙ Rainfall
Co-Authors Annisa, Illa Ari Nugroho Asriza Asriza Eko Kusratmoko Gracia, Enrico Join Wan C. Sigalingging M.H. Dewi Susilowati, M.H. Dewi Muhammad Asrofi, Muhammad Muhammad Rizqy Septyandy Pin, Tjiong Giok Priyanka Prajna Paramitha R. Syahputra Raldi Hendro Koestoer, Raldi Hendro Randhi Atiqi, Randhi Ratna Saraswati, Ratna Rudy P. Tambunan Shidiq, Iqbal Putut Ash Supriatna Supriatna Supriatna Twin Hosea Widodo Kristyanto Wiguna, Dede Prabowo Yumnaristya, Syefiara Hania