BibTex Citation Data :
@article{J.Gauss40457, author = {Marselinus Lumbanbatu and Puspita Kartikasari and Deby Fakhriyana}, title = {PERAMALAN INDEKS HARGA SAHAM GABUNGAN (IHSG) DENGAN METODE FUZZY TIME SERIES CHEN DAN CHENG}, journal = {Jurnal Gaussian}, volume = {14}, number = {2}, year = {2025}, keywords = {JCI; Forecasting; FTS Chen; FTS Cheng; Sturges; Average Based}, abstract = { The Jakarta Composite Index (JCI) is an index that measures the performance of all stocks listed on the Indonesia Stock Exchange. JCI can be used as one of the indicators used by investors to determine the movement of stocks in the Indonesian capital market. Decisions made by investors will have a stronger basis if forecasting is done. Investors can decide to exit the market or enter the market. The forecasting method used to forecast the JCI value in this study is Fuzzy Time Series (FTS). This method has advantages compared to other time series methods, where the FTS method does not require the fulfillment of classical assumptions as in ARIMA. Both forecasting methods will apply the Sturges and Average Based formulas in determining the class. The data used in this study is the JCI closing data on March 1, 2022 - March 1, 2023. The data is divided into two categories with 239 data as training data, namely data on March 1, 2022 - February 15, 2023 and 10 data as testing data, namely data on February 16 - March 1, 2023. The forecasting accuracy measure used in this study is sMAPE. Among the four forecasting methods, the best forecasting method is Cheng's Fuzzy Time Series method by applying the Sturges formula in determining the number of classes with an sMAPE value on testing data is 0.37%. }, issn = {2339-2541}, pages = {469--479} doi = {10.14710/j.gauss.14.2.469-479}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/40457} }
Refworks Citation Data :
The Jakarta Composite Index (JCI) is an index that measures the performance of all stocks listed on the Indonesia Stock Exchange. JCI can be used as one of the indicators used by investors to determine the movement of stocks in the Indonesian capital market. Decisions made by investors will have a stronger basis if forecasting is done. Investors can decide to exit the market or enter the market. The forecasting method used to forecast the JCI value in this study is Fuzzy Time Series (FTS). This method has advantages compared to other time series methods, where the FTS method does not require the fulfillment of classical assumptions as in ARIMA. Both forecasting methods will apply the Sturges and Average Based formulas in determining the class. The data used in this study is the JCI closing data on March 1, 2022 - March 1, 2023. The data is divided into two categories with 239 data as training data, namely data on March 1, 2022 - February 15, 2023 and 10 data as testing data, namely data on February 16 - March 1, 2023. The forecasting accuracy measure used in this study is sMAPE. Among the four forecasting methods, the best forecasting method is Cheng's Fuzzy Time Series method by applying the Sturges formula in determining the number of classes with an sMAPE value on testing data is 0.37%.
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