SISTEM PERINGATAN DINI PENANGGULANGAN BANJIR BERBASIS IoT

FATHUROCHMAN, RIO (2024) SISTEM PERINGATAN DINI PENANGGULANGAN BANJIR BERBASIS IoT. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

A flood is a natural disaster where excessive water conditions submerge the land. If left unchecked, flooding can lead to disease, cause environmental damage, and hinder people's mobility. To overcome the flood hazard, we need a system that can provide early warning to the public. As technology develops, utilizing IoT (Internet of Things), we can monitor water levels in an area to anticipate flood disasters. The author wishes to design a system that can monitor river conditions which have the potential to flood periodically via a smartphone in certain areas. By using IoT, we can also monitor water levels continuously and remotely. The information collected from the sensors was collected in cloud computing using a Wi-Fi module, and the graphical comprehension demonstrated data via ThinkSpeak. The Single Moving Average method uses water level and rainfall sensors as data for flood detection. This system will detect water levels and rainfall periodically. With this early warning system, it is hoped that there will be an increase in public awareness regarding weather forecasts and the dangers of flooding. Keywords: Flood, Internet of Things, ThinkSpeak, Single Moving Average Banjir merupakan bencana alam dimana terdapat kondisi air yang berlebihan sehingga merendam daratan. Jika dibiarkan banjir dapat membawa penyakit, menyebabkan kerusakan lingkungan serta menghambat mobilitas masyarakat. Untuk menanggulangi bahaya banjir tersebut, dibutuhkan suatu sistem yang dapat memberikan peringatan dini kepada masyarakat. Seiring perkembangan teknologi, Dengan memanfaatkan IoT (Internet of Things) kita dapat memantau ketinggian air di suatu daerah untuk mengantisipasi terjadinya bencana banjir. Diambil dari permasalahan yang terjadi, penulis ingin merancang suatu sistem yang dapat memantau kondisi sungai yang berpotensi banjir secara berkala melalui smartphone pada daerah tertentu. Dengan menggunakan IoT juga dapat memantau ketinggian air secara langsung dan terus menerus dari jarak jauh. Informasi yang dikumpulkan dari sensor dikumpulkan di cloud komputasi menggunakan modul Wi-Fi, dan pemahaman grafis data yang didemonstrasikan melalui ThinkSpeak. Metode Single Moving Average serta menggunakan sensor ketinggian air dan curah hujan sebagai data untuk deteksi banjir. Sistem ini akan mendeteksi ketinggian air dan curah hujan secara berkala. Dengan adanya sistem peringatan dini ini, diharapkan terjadi peningkatan kesadaran masyarakat terhadap prakiraan cuaca dan bahaya banjir. Kata kunci: Banjir, Internet of Things, ThinkSpeak, Single Moving Average

Item Type:	Thesis (S1)
Call Number CD:	FIK/SI. 24 140
Call Number:	SIK/18/24/064
NIM/NIDN Creators:	41821120024
Uncontrolled Keywords:	Banjir, Internet of Things, ThinkSpeak, Single Moving Average
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika > 004.6 Interfacing and Communications/Tampilan Antar Muka (Interface) dan Jaringan Komunikasi Komputer > 004.67 Wide Area Network (WAN)/Wide Area Network > 004.678 Internet (World Wide Web)/Internet 600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan 600 Technology/Teknologi > 620 Engineering and Applied Operations/Ilmu Teknik dan operasi Terapan > 627 Hydraulic Engineering/Rekayasa Hidrolik > 627.4 Flood Control/Pengawasan Banjir
Divisions:	Fakultas Ilmu Komputer > Sistem Informasi
Depositing User:	khalimah
Date Deposited:	31 Aug 2024 01:55
Last Modified:	31 Aug 2024 01:55
URI:	http://repository.mercubuana.ac.id/id/eprint/90936

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