Through our all stages of growing, chickens need a certain climate quality. The old climate quality is only the actual temperature-based controlling. On modern climate, an organization called Cobb-Vantress detached three climate parameters need to be satisfied: 1) temperature, 2) humidity, and 3) wind speed. It is known that those three parameters are not independent, the area to be controlled are fast area while commonly, this available tool to control those three parameters is only the speed of the exhaust fans inside the broiler house. Therefore, controlling three parameters which are intertwined each other inside a fast area with only single actuator is the main problem of this paper. The main goal is to achieve ideal microclimate control to grow chicken inside a broiler house. Alleviating those stated problem, a method that combined PID with artificial neural network is evaluated. The retrieval of the actual climate data are used as an input parameter for the process of identifying ideal climate system and used to control the climate error based-those parameters by generating wind speed to cool the broiler house. Results showed that the climate control that can be implemented effectively to maintain the effective temperature of the broiler house at 32 to 22 degrees celcius from the day-old chick to be matured in brooding stage. To achieve a steady state in the process of tuning PID should be done to get the appropriate PID parameters. Temperature controller testing shows prototype device has linear set point response between to with maximum heating rate and maximum cooling rate.
