<![CDATA[Stock price forecasting is an important aspect in financial market analysis because it can support investors in making investment decisions. This study aims to forecast the closing price of PT Bank Central Asia Tbk (BBCA) shares and compare the accuracy between the Chen and Cheng Fuzzy Time Series methods. The data used are the weekly closing prices of BBCA shares for the period January 2014 to December 2024 with a total of 566 data. The forecasting process is carried out through the stages of fuzzification, formation of fuzzy logical relationships (FLR), grouping FLRs into fuzzy logical relationship groups (FLRG), and defuzzification. Accuracy evaluation is carried out using the Mean Absolute Percentage Error (MAPE). The results show that the Chen Fuzzy Time Series method produces a prediction of BBCA's closing price in the first week of January 2025 of Rp9,440.75 with a MAPE value of 6.32%, while the Cheng Fuzzy Time Series method produces a prediction of Rp9,441 with a MAPE value of 5.74%. With a smaller MAPE value, the Cheng method is proven to be more accurate than the Chen method in predicting BBCA's closing price. This shows that giving weights to fuzzy relations in Cheng's method is able to increase the accuracy of forecasting results.]]>
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