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Naturally, a mother hen incubates her eggs until they hatch completely. However, the success rate of natural hatching is low, and hatching can be completed with a maximum of 10 eggs. Chicken farming, more specifically the chicken egg hatching system, breeders usually use an incubator for the process of hatching chicken eggs. In the incubator, there is a lamp that has been provided which is used for the process of warming the eggs so that the eggs can hatch properly and of good quality with incandescent lamps. In general, the process of hatching eggs often encounters problems or obstacles. The obstacle that is often experienced when hatching chicken eggs is that the incubator only uses incandescent lights. Therefore, to avoid this problem, a microcontroller was designed to overcome this problem. This tool is a combination of a microcontroller with an Arduino-based temperature and humidity sensor. With this tool, after the eggs hatch, when the lights are off, the sensor can read the output in the form of the incubator temperature, which is detected by the Arduino serial display. Design methods and experimental methods were used in this research. Tool testing is divided into three types, namely temperature testing, humidity testing and egg load testing. The result of this research is an automatic egg incubator machine that uses Arduino. Several electronic components used in the incubator are Arduino,

Control and monitoring systems that use the Internet-of-Things (IoT) can be found in everyday life, for example, in smart home applications, smart transportation, and smart cities. IoT-based monitoring of environmental conditions both indoors and outdoors is generally carried out to reduce the risk of unwanted events. One example of an unwanted event is a fire. Fires can occur in houses, office buildings, rice fields, or forests. In order to help provide early warning of a flame that can cause a fire, this study aims to design and implement an IoT-based fire detection and warning system using the NodeMCU ESP8266 and a flame sensor. The sensor used is an infrared sensor that will detect infrared light radiation coming from a fire. The test results show that the system successfully detects the presence of fire up to 50 cm from the fire sensor and can be monitored via thinger.io. Additionally, notifications from thinger.io via e-mail and Telegram to users were successfully executed.

Solar energy is a potential solution to meet the electricity needs of TNI AD posts and bases in border areas. However, conventional solar energy systems have limited efficiency because they can only absorb sunlight from one direction. The efficiency of solar energy systems can be improved by using a dual-axis tracking system equipped with a LDR sensor. The LDR sensor is used to detect the direction of sunlight. The change in the LDR sensor resistance due to the change in the intensity of light that hits it is then processed by a microcontroller to move the solar panel in the appropriate direction. Based on the results of testing, the dual-axis tracking system with an LDR sensor significantly increases the power generated compared to conventional solar energy systems. At the peak of performance during dynamic testing at 12:00 pm, the total power reached 2,196 W, while the static test reached a total power of 1,311 W. Therefore, the dual-axis tracking system with an LDR sensor can be a more optimal choice to improve the performance and efficiency of solar energy systems in generating electricity at TNI AD posts and bases in border areas.

The community's need for electric power is increasing and efforts to monitor electric power are to obtain information on the results of measurements of voltage and electric current. Based on the analysis of the measurement results, it can be concluded that (1) the current measurement is more optimal when using the SCT-013 current sensor, (2) the voltage measurement is more optimal when using the PZEM-004T voltage sensor, (3) the difference in measurements using the current sensor is greater than the difference with a voltage sensor.