<![CDATA[Every year, Udayana University publishes the Non-Tax State Revenue Target (TPNBP) as a guide for allocating budgetary funds for the T+2 year. The provision of budget allocations for the T+2 year will depend on how accurately the TPNBP is calculated, which will boost efficiency in carrying out budget planning. Due to the limits of the PNBP realization data at Udayana University and the benefits of the ANFIS approach for forecasting stationary data types, it is required to evaluate the merits of the Gray-Markov and ANFIS methods in order to determine which method is more effective. The study's findings reveal that the Grey-Markov approach yields a value of 0.118% while the ANFIS method yields a value of 4.978%. This suggests that while both methods produce extremely precise results, the Grey-Markov method is more accurate than the ANFIS method due to its smaller MAPE value. The MAPE value for the Grey-Markov approach for the SPI acceptance variable is 0.319%, whereas the MAPE value for the ANFIS method is 23.39%, indicating that the Grey-Markov method is more accurate at predicting SPI acceptance. Keywords : ANFIS; Grey-Markov; Forecasting; PNBP]]>
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