Modeling Monthly Rainfall in Malang using Long Short Term Memory

Eni Sumarminingsih; Suci Astutik; Nur Silviyah Rahmi; Aqsa Yudhistira Redi; Natasha Aulia

doi:10.2991/978-94-6463-525-6_18

<Previous Article In Volume

Next Article In Volume>

Modeling Monthly Rainfall in Malang using Long Short Term Memory

Authors

Eni Sumarminingsih¹^{, *}, Suci Astutik¹, Nur Silviyah Rahmi¹, Aqsa Yudhistira Redi¹, Natasha Aulia¹

¹Universitas Brawijaya, Malang, Indonesia

^*Corresponding author. Email: eni_stat@ub.ac.id

Corresponding Author

Eni Sumarminingsih

Available Online 29 October 2024.

DOI: 10.2991/978-94-6463-525-6_18 How to use a DOI?
Keywords: Modeling; Rainfall; Long Short Term Memory
Abstract: Malang Regency has the potential to experience flooding. The flood was caused by the high rainfall that occurred in the area. The purpose of this study is to model monthly rainfall at three stations in Malang, namely Abd. Saleh, Karangkates station and Karangploso station use Long Short Term Memory (LSTM). The results of this study (1) The best model for monthly rainfall at Station Abd. Saleh uses Station And rainfall input. Saleh lag 6, (2) The best model for monthly rainfall at Karangploso Station using rainfall input at Karangploso Station lag 6 and (3) The best model for monthly rainfall at Karangkates Station using rainfall input at Karangkates Station lag 1, lag 4 and lag 6, rainfall at Abd. Saleh Air Base Station lag 1, lag 4 and lag 6 as well as rainfall at Karangploso Station lag 1, lag 4 and lag 6.
Copyright: © 2024 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.

Download article (PDF)

<Previous Article In Volume

Next Article In Volume>

Volume Title: Proceedings of the 2023 Brawijaya International Conference (BIC 2023)
Series: Advances in Economics, Business and Management Research
Publication Date: 29 October 2024
ISBN: 978-94-6463-525-6
ISSN: 2352-5428
DOI: 10.2991/978-94-6463-525-6_18 How to use a DOI?
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.

Cite this article

ris enw bib

TY  - CONF
AU  - Eni Sumarminingsih
AU  - Suci Astutik
AU  - Nur Silviyah Rahmi
AU  - Aqsa Yudhistira Redi
AU  - Natasha Aulia
PY  - 2024
DA  - 2024/10/29
TI  - Modeling Monthly Rainfall in Malang using Long Short Term Memory
BT  - Proceedings of the 2023 Brawijaya International Conference (BIC 2023)
PB  - Atlantis Press
SP  - 156
EP  - 166
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-525-6_18
DO  - 10.2991/978-94-6463-525-6_18
ID  - Sumarminingsih2024
ER  -

download .riscopy to clipboard