Fuzzy Time Series Model Lee dalam Memprediksi Nilai Ekspor di Indonesia
DOI:
https://doi.org/10.33998/processor.2024.19.2.1794Keywords:
Data mining; Fuzzifikasi; Fuzzy; Fuzzy Time Series; Peramalan; PrediksiAbstract
− Exports are an important indicator in the Indonesian economy. In April 2022, the Central Bureau of Statistics (BPS) reported that Indonesia's export value reached USD 27.32 billion, an increase of 47.76% compared to the previous month. Unstable export values are influenced by exchange rate fluctuations, changes in market demand, and other external factors, making business planning and trade between countries difficult. This study aims to predict the value of Indonesian exports using Lee's Fuzzy Time Series method and measure its accuracy with Mean Absolute Percentage Error (MAPE). The data used is secondary data from BPS, covering export values from January 2021 to February 2024. The steps in this method include determining the universe set, interval formation, fuzzy set, fuzzification of data, determination of Fuzzy Logic Relationship (FLR), formation of Fuzzy Logic Relationship Group (FLRG), defuzzification, and prediction results. the results showed that prediction with Fuzzy Time Series Lee has an error rate of 5.1568% (MAPE), which is in the excellent category. The predicted value of Indonesia's exports for March 2024 is US$ 21,850.69 million.
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