The development of technology in the field of fisheries is very rapid along with facilitating human work in the field. Human work can be done by tools such as feeding catfish in ponds automatically. This job is easy to do, but problems will arise when catfish are not fed at night or are fed too late, then the catfish will eat smaller catfish so that it can be detrimental to catfish farming owners. With this background, the author created a "Catfish Feeding Control System Based on the Internet of Things (IoT) Using the Fuzzy Sugeno Method". This testing and discussion was carried out by functionally testing each component, testing the program using simulation and testing it as a whole. The results of testing the tool and taking data are expected to obtain valid data and the tool works according to its function and purpose as expected. From the results of the analysis and discussion of the research entitled "Internet Of Things (IoT) Based Catfish Feeding Control System Using the Fuzzy Sugeno Method" it can be concluded as a process of automatic fish feeding using the RTC module as a reference for catfish time three times a day with good results and the process of calculating the amount of fish feed 3 to 8% with fish weight from LOW to HIGH using Fuzzy Sugeno has worked well compared to the results of the BLYNK application.

This research aims to design an Aircraft Jacking control system for the Boeing 737-800 to automatically balance the aircraft's inclination using an MPU6050 sensor and servo actuators. The system can detect pitch and roll angles with an accuracy of ±0.5° and an average response time of 150 ms. Based on tests using five datasets, the balancing time ranges from 400 to 600 ms, depending on the initial imbalance. In Dataset 5, with a pitch of 3.5° and a roll of -2.3°, the system required 600 ms to achieve balance, demonstrating its ability to handle critical conditions. The servo actuators successfully adjusted the jacking height within a range of 2 cm with a precision of ±0.02 cm, while the OLED-based monitoring system allowed operators to observe the inclination angles in real-time. Furthermore, ESP-NOW-based communication achieved a data transmission success rate of 98%, supporting efficient centralized control. This research demonstrates the system's effectiveness in balancing the aircraft quickly and accurately, providing a foundation for further development under extreme conditions and energy efficiency improvements.