During the COVID-19 pandemic since early 2020 in Indonesia, the demand for electrical energy in the housing sector has increased significantly. This is due to the government’s recommendation to reduce activities on the outside and work from home, specifically for educational and entertainment activities. Those are almost recommended to be done online. Many people complain about the increase in monthly electricity payments compared to before the pandemic. The construction of solar power plants in housing/solar home systems (SHS) will reduce the electricity consumption from the public grid. This SHS installation can be used to supply some household electricity needs, such as computers, televisions, internet facilities, lighting, et cetera. In this article, the researchers discuss the performance testing of SHS with a capacity of 300 Wp. It is installed in the house buildings accompanied by the design and measurement of solar energy potential.

This article discusses the design of a hydroponic planting process monitoring system based on the internet of things. This device uses an ESP32 microcontroller board as the main controller. The parameters that were monitored and acquired were the conditions of the hydroponic growing media. Those parameters are; water pH, water temperature, water turbidity level, and ambient air temperature and humidity. The five parameters are measured by analog sensors integrated with the ESP32. These parameters affect the growth process and the quality of crop yields. This article also describes the calibration method for each sensor used for parameter measurement. Then the monitoring of these parameters is carried out by utilizing a real-time database, namely Google Firebase. This platform is very suitable for all IoT-based monitoring and control applications. Measurement result data is uploaded and saved to the real-time database. Then paired by Android-based applications. This application was created to be used by hydroponic farmers who use this device. Thus the results of monitoring can be used to optimize the process of growing hydroponic plants.

<span lang="EN-US">The characteristics of the photovoltaic module are affected by the level of solar irradiation and the ambient temperature. These characteristics are depicted in a V-P curve. In the V-P curve, a line is drawn that shows the response of changes in output power to the level of solar irradiation and the response to changes in voltage to ambient temperature. Under partial shading conditions, photovoltaic (PV) modules experience non-uniform irradiation. This causes the V-P curve to have more than one maximum power point (MPP). The MPP with the highest value is called the global MPP, while the other MPP is the local MPP. The conventional MPP tracking technique cannot overcome this partial shading condition because it will be trapped in the local MPP. This article discusses the MPP tracking technique using an evolutionary algorithm (EA). The EAs analyzed in this article are genetic algorithm (GA), firefly algorithm (FA), and fruit fly optimization (FFO). The performance of MPP tracking is shown by comparing the value of the output power, accuracy, time, and tracking effectiveness. The performance analysis for the partial shading case was carried out on various populations and generations.</span>

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Hydroponics is one of the agricultural techniques with great potential to produce plant products. Hydroponics is also a pattern of plant breeding that is environmentally friendly and does not require a large area of ​​land. Although it has been developed for long time ago, the quality and quantity of hydroponics does not really give significant results. In order to improve the quality of agricultural products, a modernization step is needed by implementing an automation system based on Internet of Things. Thus, the solution offered to overcome the problems of the current hydroponic system, the innovation offered is green hardware, namely Airlangga Sahabat Petani Hidroponik (Arsenik). In this hardware, monitoring of the system with an integrated manner and measuring several aspects such as environmental and soil levels, nutrients in plants and interpreting them into an output that can be read directly by users. The expected result through this hardware is community empowerment in developing hydroponic systems and maximum hydroponic plant yields.