Modeling of Arima and Fuzzy Time Series Saxena Easo in Forecasting the Stock Price of PT. Indofood Sukses Makmur Ltd

Stock is one of the most popular investment instruments due to its ability to provide attractive benefit. One widely recognized company with a strong position both domestically and globally is PT. Indofood Sukses Makmur Ltd. It is also included in the IDX30 index. Investor require forecasting method as a basis for making informed decisions in response to stock price fluctuation. This study aims to model Autoregressive Integrated Moving Average (ARIMA) and Fuzzy Time Series (FTS) Saxena Easo, and to determine the best method based on the lowest RMSE value. The data used is sample data of daily closing stock prices from March 2023 to October 2024. The dataset is divided into 377 training data points and 19 testing data points. For the ARIMA method, the model that satisfy all assumptions and yields the lowest RMSE value is ARIMA (1,1,0), with an RMSE value equal 78.2319. The FTS Saxena Easo uses fuzzy logic produces an RMSE is 3.0619. The result shows that the RMSE value of the FTS Saxena Easo is lower than ARIMA (1,1,0), so FTS Saxena Easo is chosen as the best method. Forecasting using FTS Saxena Easo produces a Mean Absolute Percentage Error (MAPE) equal 0.0063%. Since the MAPE value is less than or equal to 10%, FTS Saxena Easo is considered very good for forecasting the closing price of PT. Indofood Sukses Makmur Ltd.