Forecasting of Indonesia Seaweed Export: A Comparison of Fuzzy Time Series with and without Markov Chain

Andi Sri Bintang, Wen-Chi Huang, Rosihan Asmara
  AGRISE,Vol 19, No 3 (2019),  155-164  
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Abstract


This study compared Fuzzy Time Series with and without Markov Chain Method for forecasting Indonesian seaweed export in particular; it analyzed the forecasting ability of the models and the effects of different lengths of interval and increment information on the forecasting error of models. The secondary data between 1989 and 2018 were collected from Bureau Central Statistic (BPS), UN Comtrade, Ministry Marine and Fisheries (KKP). The results indicate that Fuzzy Time Series with and without Markov Chain method performs better in the forecasting ability in short-term period prediction and the values of Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE) tends to be smaller than the Fuzzy Time Series without Markov Chain.

Keywords


Seaweed export; Forecasting; Fuzzy Time Series; Markov Chain

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DOI: https://doi.org/10.21776/ub.agrise.2019.019.3.4

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