Implementation of RMS Prop Algorithm for Flood Prediction Using Rainfall, Air Temperature, Humidity, Wind, and Tides Data

DOI

10.2991/978-2-38476-483-9_31How to use a DOI?

Keywords

Flood; Prediction; RMS Prop; Rainfall; Wind

Abstract

Climate change will occur in Indonesia in 2024, especially in the Kudus, Demak and Pati areas, there will be major flooding which will cause 20,772 refugees spread across 59 refugee camps, 93,149 people will be affected by the flood, and there will be 4 deaths. This research aims to predict flood-prone areas in the Demak area and its surroundings based on rainfall, air temperature, humidity, wind and tides, using training data in 2023 and test data in 2024 using the RMS Prop algorithm to predict and test accuracy. And determine the RMSE value. This research uses the python-based RMS Prop algorithm method with data used from the meteorology, climatology and geophysics agency for the Class II Maritime Tanjung Emas Semarang meteorological station. The research results obtained in this study were by conducting the experiment 8 times using a number of epochs of 10, 20, 30, 40, 50, 60, 70, 80 which resulted in the best average and lowest RMSE value at a number of epochs of 30 with the research conclusion being accuracy results of 94.4% and an RMSE value of 0.7090, it can be concluded that the RMS Prop algorithm is able to predict floods well based on rainfall, temperature air, humidity, wind, and tides.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - R. Hadapiningradja Kusumodestoni
AU  - Agus Subhan Akbar
AU  - Fandy Indra Pratama
AU  - Muhammad Ilma Akhis
AU  - Ahmad Frediyansyah
AU  - Teguh Tamrin
AU  - Adi Sucipto
PY  - 2025
DA  - 2025/11/17
TI  - Implementation of RMS Prop Algorithm for Flood Prediction Using Rainfall, Air Temperature, Humidity, Wind, and Tides Data
BT  - Proceedings of the Jepara International Conference on Education and Social Science 2024 (JIC 2024)
PB  - Atlantis Press
SP  - 245
EP  - 251
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-483-9_31
DO  - 10.2991/978-2-38476-483-9_31
ID  - Kusumodestoni2025
ER  -