Disaster Early Warning System berbasis Artificial Intelligence

Analkhair, Raja and Syaddad, Anwar and Ardiansyah, Muahammad Farisi and Anuruddin, Muhammad Yahya (2023) Disaster Early Warning System berbasis Artificial Intelligence. Undergraduate thesis, Universitas Muhammadiyah Malang.

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Natural disasters are a serious threat to human life and the environment. One way to reduce the impact of disasters is to use an effective early warning system. In recent years, advances in artificial intelligence (AI) have opened up new opportunities in the development of more accurate and responsive disaster early warning systems. This study contains a design plan for an Artificial Intelligencebased Disaster Early Warning System, which is a system that functions to provide early warning to local residents regarding rivers that have the potential to cause flood disasters. Artificial Intelligence is used to predict river water levels from several streams that have been analyzed. There are three methods used in this discussion, namely; RBFNN, LSTM, and SVR. This research makes an important contribution in the development of a more sophisticated and reliable disaster early warning system. The use of artificial intelligence in early warning systems can help authorities and the public take appropriate preventive measures, reduce human and material losses, and speed up the post-disaster recovery process.

Item Type: Thesis (Undergraduate)
Student ID: 201910130311135
Keywords: early warning systems, artificial intelligence, natural disasters, flood disaster predictions.
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Faculty of Engineering > Department of Electrical Engineering (20201)
Depositing User: 201910130311135 muhyahyaan
Date Deposited: 13 Jan 2024 01:16
Last Modified: 13 Jan 2024 01:16
URI: https://eprints.umm.ac.id/id/eprint/2539

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