Optimization of Forest Plant Seeding Based On the Internet of Things

Abstract The research objective is to compare the seeding of forest plants using manual methods with the Internet of things-based seeding. The research method used a prototyping model. In this research, the application of the Internet of Things is supported by solar panels that are used as alternatives energy if at some time conventional energy has decreased power or disconnected. Thus, the use of tools connected to each other can continue to run without worrying about losing power. Some of the parameters measured in this seeding include room temperature, soil pH, and soil humidity. Sensor equipment used includes temperature sensors, Soil Moisture Sensor, and soil pH sensors. The temperature sensor is used as a trigger to turn on the blower that serves to remove heat from the room. Besides, the moisture sensor is used as a trigger to turn on the water pump used as an automatic sprinkler of crop seeds. Then, soil pH sensors are used to measure soil acidity levels that affect the growth of forest plant seeds. As for the seeding process is done using Mangium type plant seed or in Latin “Acacia Mangium” by using 400 seed samples. The results of this study showed that there was an increase in seed growing during seeding supported by the Internet of Things method of 24% compared to manual methods.