摘要： Photovoltaic system has uncertain output in generating electrical energy, as it is intensely influenced by different weather condition. This modeling system applies an Adaptive Neuro-Fuzzy Inference System (ANFIS) technique to gain data of power prediction, voltage, current, and temperature. The mathematical representation of the photovoltaic using Matlab/Simulink setting has been developed and presented by using the photovoltaic basic solar irradiation effect and temperature changes. This model is divided into two systems run by ANFIS; ANFIS 1 and ANFIS 2. The design of ANFIS is expected to update its parameter to determine errors between output and target. MAPE (Mean Absolute Percentage Error) value for ANFIS 1 test of open circuit output voltage was 0.0104. This MAPE score is found to be excellent predictive data with less than 10% MAPE value. For the ANFIS 2 test, the AC output voltage was 0.026%, output current of 1.3035%, and 0.0046% of frequency. Based on the MAPE scores, very suitable data prediction has been produced with less than 10% MAPE value. Briefly, this study reveals that the ANFIS technique yields load prediction results that can improve the accuracy and rapidness of prediction as well as very minimum errors.