Energy Harvesting Berbasis Panel Surya untuk Keberlanjutan Daya Sensor IoT - Prayitna, Adiyuda; Buwono, Robby Cokro (Algoritme Jurnal Mahasiswa Teknik Informatika, 2025)
The utilization of the Internet of Things (IoT) in the fields of environmental monitoring or precision agriculture is often constrained by power supply issues for wireless sensors. This study explores solar energy harvesting solutions as a standalone power source for IoT data logging systems. Through the analysis of solar energy production datasets, this study measures the conversion efficiency of solar panels, predicts daily energy availability, and tests their feasibility to meet the needs of energy-efficient wireless communication-based sensors.The results show that the conversion efficiency of solar panels is relatively stable despite being affected by external factors such as weather. The ARIMA model proved superior in predicting energy production with an MAE accuracy of 792,878.69 kWh, beating the linear regression approach. Simulation of the power demand of the IoT sensor (0.024 kWh/day) also confirmed that the energy produced by the solar panel (millions of kWh/day) far exceeds the operational demand. These findings prove that solar energy harvesting systems are feasible for IoT applications in remote locations, while opening up optimization opportunities through adaptive power management.