<![CDATA[The use of electrical energy in boarding houses often results in unintentional energy waste, because residents tend to leave their rooms without unplugging electrical devices, which causes increased electricity consumption and higher costs. This study aims to design an IoT-based electrical energy monitoring and control system for boarding rooms. This system uses an ESP32 microcontroller connected to a WiFi network, while the energy meter is equipped with a PZEM-004T sensor to measure electrical energy parameters. Measurement data is transmitted to a database for monitoring purposes and displayed on the user's website. This study applies the third-order Moving Average forecasting method by utilizing energy measurement data obtained from the PZEM-004T sensor, which is processed by a web server. The forecasting results show good accuracy, with errors ranging from 0.99–18.65% compared to the actual values. Furthermore, the measurement results show satisfactory performance, with parameter measurement errors ranging between 0–0.8%. This system is capable of providing accurate information about electrical energy consumption, estimating remaining electrical energy, and issuing notifications when available electrical energy falls below a predetermined threshold. Therefore, the proposed system is considered reliable and accurate for monitoring, controlling, and predicting electrical energy, thus supporting efficient energy management.Keywords – 3rd order Moving Average, Energy Monitoring, ESP32, Forecasting, Internet of Things.]]>
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