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<title>Early Warning System And Monitoring Of River Water Quality Based On Internet Of Things</title>
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<name type="Personal Name" authority="">
<namePart>Mokhamad Hendayun</namePart>
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<name type="Personal Name" authority="">
<namePart>Vito Hafizh Cahaya Putra</namePart>
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<namePart>Purnomo Yustianto</namePart>
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<publisher>DEVOTION</publisher>
<dateIssued>2021</dateIssued>
<issuance>monographic</issuance>
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<note>River conditions in Bandung City are currently in critical condition. This study aims to create an early warning system and monitoring of river water quality 
based on the Internet of Things in the hope that early warnings sent through the telegram application belonging to the Bandung City DLHK officer and the Twitter 
social media website, can inform the Bandung City DLHK officer that a river is in a polluted condition and the officer can immediately go to the location of river 
water to carry out mitigation, and give warnings to the community. The research method used using the waterfall method which consists of: needs analysis, system 
design, implementation, testing, and maintenance with sequential implementation. Data collection methods were carried out in several ways, namely: interviews, 
giving questionnaires, and literature studies used in this study sourced from books, journals, seminar presentations, and the internet as references in the research 
conducted. Based on the research that has been carried out, the following test results are obtained: black box testing is carried out in accordance with those 
contained in the test plan with the results of each test having valid results. The results obtained from the user acceptance test which are calculated using the 
Likert scale have an average value of 86.94% which fall into the category of strongly agree, and there are three guidelines which are a follow-up to the output 
of the early warning system that can be carried out either by the Environmental Service. and Cleanliness (DLHK) of Bandung City and the community.</note>
<subject authority=""><topic>Early Warning System,  Internet of Things, Water  </topic></subject>
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