DESIGN AND BUILD OF LIQUID WASTE AERATOR CONTROL BASEDON ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS)

Liquid waste from the production process can pollute the environment if disposed of directly, so it must be managed professionally. Liquid waste treatment is generally carried out biologically BOD (Biological Oxygen Demand) using decomposing bacteria or chemically or COD (Chemical Oxygen Demand). Wastewater treatment, both BOD and COD, requires oxygen to ensure that the quality of liquid waste is safe. In most wastewater treatment plant, the aerator machine is an air pump used to produce high-pressure air in liquid waste containing oxygen (O2). Based on preliminary research on the problem, in general, the aerator work operation is carried out manually on average 11-17 hours a day. Operating the aerator machine manually, especially at a large capacity, will cause the use of electrical energy to be wasteful. Based on the problemsabove, further research will be carried out on how to determine the optimal working time of the aerator andnot cause excessive energy consumption but the liquid waste produced is still within safe limits. The research was conducted to design an intelligent microcontroller-based tool with a long output aerator operating time on the input characteristics of liquid waste. This control system uses the adaptive neural fuzzy inference system (ANFIS) method, because ANFIS can solve all kinds of complex and nonlinear problems effectively. The input variables used are COD reduction and waste volume while the output is thelong operating time of the aerator. The results obtained, the system design can be implemented properly and according to the setting point with an average operating time of 7.6 hours aerator working hours and can reduce the use of electrical energy by 31%.