A control rod worth prediction using Adaptive Neuro-Fuzzy Inference System for Pre-Calibration Method at TRIGA PUSPATI Reactor

•Development of ANFIS as pre-calibration method to determine the control rod’s worth.•11 ANFIS model were generated based on different types of input partitioning methods.•Prediction of Safety rod worth is excellent with 0.0156 and 0.0204 of MAE and RMSE.•Prediction of Regulating rod worth is less accurate; the prediction not following the actual trend. One of the control rod calibration methods in research reactors is the doubling time. However, this method reduces the operation time and limits the number of research activities. A pre-calibration method is proposed in this study by utilizing an ANFIS method. Two data inputs based on the annual rod worth, and the worth drop of the Shim and Transient rods were collected to predict the Safety and Regulating rod's worth. The results showed that ANFIS can predict the Safety rod worth with the lowest MAE and RMSE errors of 0.0156 and 0.0204 while 0.0616 of the percent error. For the Regulating rod's worth, the predicted and actual output data were less accurate due to the composition of air in the Transient rod. Nevertheless, the utilization of ANFIS as the pre-calibration method for control rod calibration at research reactors could be implemented and optimized in future studies.