Automatic Filterization For Industrial Drinking Water Quality Based On Internet Of Things Sistem Monitoring Filterisasi Air Minum Industri Berbasis Internet Of Things

Main Article Content

Alifia Novita
Elta Sonalitha
Subairi

Abstract

Water that suitable for consumption must comply with several biological, chemical and radioactive requirements. The majority of people not understand the quality of the water they consume, most people only recognize clean and dirty water, without knowing the suitability of this water. Because not all substances contained in water can be seen with the naked eye, so it will be difficult to know whether the water is in accordance with the quality of drinking water or not. This study was aimed at monitoring several drinking water quality parameters in the form of pH (6.5 - 8.5), Turbidity (<5 NTU) temperature (22 - 27 ) and TDS (<500 ppm) using pH sensors, turbidity sensors temperature sensors and TDS sensors, and Ultraviolet light as an inhibitor of bacterial growth. The resulting data is executed by NodeMCU 8266 and forwarded via IoT to be sent to the server and forwarded to the application automatically. The results of the pH sensor readings show a reading accuracy of up to 98.36%, the temperature sensor the reading accuracy reaches 96%, the turbidity sensor has an accuracy level of up to 90.1%, while the TDS (Total Dissolve Solid) sensor has an accuracy level of 95, 16%. Water from the filtration of the water filter can be categorized as suitable for consumption accordance with drinking water standards in the Decree of the Minister of Health No.492 of 2010.

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Article Details

How to Cite
[1]
A. Novita, E. Sonalitha, and Subairi, “Automatic Filterization For Industrial Drinking Water Quality Based On Internet Of Things”, PELS, vol. 1, no. 2, Jul. 2021.
Section
Electrical Engineering

References

[1]. U. P. D. Arindita, H. Hudiono, and F. A. Soelistianto, “RANCANG BANGUN SISTEM FILTERISASI UNTUK MONITORING KUALITAS AIR MINUM RUMAH TANGGA,” J. Jartel J. Jar. Telekomun., vol. 8, no. 1, p. 7, 2019.
[2]. M. A. Nugroho and M. Rivai, “Sistem Kontrol dan Monitoring Kadar Amonia untuk Budidaya Ikan yang Diimplementasi pada Raspberry Pi 3B,” J. Tek. ITS, vol. 7, no. 2, pp. 3–8, 2019, doi: 10.12962/j23373539.v7i2.30920.
[3]. E. E. Barus, R. K. Pingak, and A. C. Louk, “OTOMATISASI SISTEM KONTROL pH DAN INFORMASI SUHU PADA AKUARIUM MENGGUNAKAN ARDUINO UNO DAN RASPBERRY PI 3,” J. Fis. Fis. Sains dan Apl., vol. 3, no. 2, pp. 117–125, 2018, doi: 10.35508/fisa.v3i2.612.
[4]. A. G. L. Boro, A. B. Setiawan, and W. Dirgantara, “Penjadwalan Pakan Dan Pengendalian Suhu Pada Kandang Babi Secara Otomatis Berbasis Arduino (Automatic Feeding Schedule And Temperature Controlling In Pig Cage Based On Arduino),” JEEE-U (Journal Electr. Electron. Eng., vol. 3, no. 2, pp. 264–278, 2019.
[5]. V. Isnainy, E. S. Budi, and H. Hardjono, “Pengontrolan pH Menggunakan Algoritma Logika Fuzzy pada Pengolahan Limbah Cairan Kimia,” J. Elektron. dan Otomasi Ind., vol. 4, no. 3, pp. 39–44, 2020.
[6]. D. A. Ula, “Rancang bangun sistem monitoring kualitas air layak minum berbasis internet of things dengan metode Fuzzy Tsukamoto sebagai sistem pendukung keputusan.” Universitas Islam Negeri Maulana Malik Ibrahim, 2020.
[7]. P. U. Indonesia, “No Title,” Pureit #GivePureLove, 2017. https://www.unilever.co.id/news/press-releases/2017/pureit-givepurelove.html (accessed Feb. 03, 2021).
[8]. F. Budiman, M. Rivai, and M. A. Nugroho, “Monitoring and Control System for Ammonia and pH Levels for Fish Cultivation Implemented on Raspberry Pi 3B,” in 2019 International Seminar on Intelligent Technology and Its Applications (ISITIA), 2019, pp. 68–73.
[9]. S. A. Kurniatuty and K. A. Widodo, “Rancang Bangun Sistem Kontrol Pakan Ikan dan Kekeruhan Air yang Dilengkapi Dengan Monitoring Kualitas Air Berbasis Internet of Things ( IoT ),” Informatika, vol. 02, no. 01, pp. 1–5, 2015.