Automatic Chicken Feeding Machine Using Fuzzy Inference System - Islamiyah, Mufdatul; Maisaroh, Maisaroh (Jurnal Riset Teknologi Pencegahan Pencemaran Industri, 2025)
Efficient feed management is a crucial factor in increasing chicken farm productivity. However, manual feeding systems are often inconsistent and labor-intensive. To address these issues, this study designed and implemented an automatic chicken feeder equipped with a fuzzy inference system, where the fuzzy system plays a role in processing sensor data. The sensors used in this research are temperature sensors, ultrasonic, RTC, electric motors and microcontrollers. This system can automatically determine the timing and amount of feed given based on parameters such as time, number of chickens, and the level of remaining feed in the container. The fuzzy method is used because it can handle uncertain and variable input data and allows for more flexible decision-making. System testing was conducted using MATLAB simulations to test the fuzzy logic response to feed quantity and input conditions. In addition to simulation testing, hardware testing was also conducted to ensure that all physical components of the automatic chicken feeder functioned properly and directly according to the feed design. The simulation results showed that the defuzzifier value was 10, thus concluding that the motor movement of the device was categorized as moderate  and also demonstrated that the system can provide feed in a timely and appropriate manner, while reducing feed waste. Thus, this tool has the potential to help farmers save time, operational costs, and improve feed efficiency.