@article{Widiasari_Zulkarnain_2021, title={Rancang Bangun Sistem Monitoring Penggunaan Air PDAM Berbasis IoT}, volume={7}, url={https://jurnal.pcr.ac.id/index.php/jkt/article/view/5152}, DOI={10.35143/jkt.v7i2.5152}, abstractNote={<p><em>Water is one of the most important sources of life. One way to save water is by monitoring the flow of water consumed per month. The flow rate measurement is applied to every household that uses the PDAM, so that each house is installed a water meter, which is used to measure or record the volume of water that has been used for each household’s needs. The measurement of the volume of water contained in the water meter is used to determine the number of tariffs that must be paid by each household to the PDAM every month of use. In this research, a system is made that can monitor the quality and use of PDAM water. In this system, a turbidity sensor is used which will measure the level of water turbidity in NTU units. This NTU value will show the quality of PDAM water whether it is suitable for use in daily needs or not. The water flow sensor will be installed in the middle of the PDAM pipe, the water flow data measured on the sensor will be processed on the Arduino Uno module to be converted into data for the estimated cost of using PDAM water. Furthermore, all data will be displayed on the LCD, namely data on the level of water turbidity, data on the amount of water discharge and the estimated cost to be paid by the customer. All data will be sent to the blynk server via ESP32 Camera. The data stored on the server can be accessed using the blynk application on a smartphone. In addition, the data will also be stored on the SD Card as a data backup. The results of the turbidity sensor readings show a water turbidity value of 5 NTU. The error value of the water flow sensor readings is 1.6%, which means the accuracy rate is 98.4%. While the data from the reading of the PDAM water usage costing system has no errors so that the data accuracy reaches 100%.</em></p>}, number={2}, journal={Jurnal Komputer Terapan}, author={Widiasari, Cyntia and Zulkarnain, Laxsmana Anugrah}, year={2021}, month={Nov.}, pages={153–162} }