OPTIMIZATION THE COAGULATION PROCESS AT WATER TREATMENT PLANTS (WTP) OF REGIONAL DRINKING WATER COMPANIES USING NEURAL NETWORKS AND INTERNET OF THINGS (IOT)

• Main Author: Putro Wibisono, Radityo
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/55531
• Institution: Institut Teknologi Bandung

Drinking water can be said to be feasible for consumption if it meets the water quality standards in accordance with the Minister of Health of Republic of Indonesia Regulation No.492/2010 on Requirements for Drinking Water Quality. drinking water is a primary need to support life. Approximately 70% of the availability of drinking water in big cities is supported by the Regional Water Company (PDAM). Currently, there are still many PDAMs that use manual methods to monitor the quality of raw water and its processing, so that the quality of the output is less awake. Raw water is the source of source that will be processed by PDAM, which then the results of processed in the form of drinking water will be distributed to drinking water consumers receorded in PDAM. In this thesis, is built a system prototype that can measure the quality of raw water using sensors, and predicts the need for chemicals or coagulants for water treatment in Water Treatment Plant (WTP) buildings by utilizing Internet of Things (IoT) communications. The sensor used can measure several water quality parameters including pH to determine the level of acidity or alkalinity of water, Dissolved Oxygen (DO) to determine dissolved oxygen levels in water and turbidity to determine levels of turbidity in water. System processing is carried out by a microcontroller. The Artificial Neural Network (ANN) method is used to calculate the number of coagulants needed for the water treatment process, which will be used by consumers. This system can predict the need for chemicals or coagulants for automatic water treatment with 3 (three) main parameters, including pH, DO, and turbidity, besides that the system can also display raw water quality measurement data, coagulant data, and water pump discharge data by utilizing IoT communication. By using this system, the use of coagulant materials is more efficient and the quality of treated water does not fall out of the predetermined range of values. This reduces the possibility for PDAM consumers to use water with quality beyond standard limits.