<![CDATA[This study aims to develop an online integrated monitoring system for photovoltaic (PV) or solar panels using Arduino, the Internet of Things (IoT), and the Blynk digital application. The developed system is used to collect data for further testing of measurable variables, including voltage, current, and power. This study employs a descriptive-associative research design with a three-predictor regression analysis method. The variables are classified into two categories: measured variables and research variables. The research sample consists of 70 time-series data points. The monitoring system was developed by integrating an ACS712 current sensor, a voltage sensor, and a DHT22 sensor with Arduino programming connected to a Wi-Fi module and NodeMCU, while the Blynk platform was used to display the monitoring results. The study began with the design of the software and hardware components, followed by system performance testing and hypothesis testing to determine the significance of and relationships among the research variables. To evaluate the feasibility of the developed system, sensor accuracy was analyzed using the Mean Absolute Percentage Error (MAPE) method. The test results demonstrated the measurement accuracy of the developed digital solar monitoring system compared with conventional manual measuring instruments. The MAPE values obtained for current and voltage were 9.9% and 2.2%, respectively. These error values met the testing requirements and were classified as having a very good level of accuracy.]]>
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