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    An Algorithm of Saxena-Easo on Fuzzy Time Series Forecasting

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    F. MIPA_Jurnal_Ahmad Kamsyakawuni_An algorithm of Saxena-Easo on fuzzy time.pdf (2.538Mb)
    Date
    2018-04-27
    Author
    RAMADHANI, Lutvia C.
    ANGGRAENI, Dian
    KAMSYAKAWUNI, Ahmad
    HADI, Alfian Futuhul
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    Abstract
    This paper presents a forecast model of Saxena-Easo fuzzy time series prediction to study the prediction of Indonesia inflation rate in 1970-2016. We use MATLAB software to compute this method. The algorithm of Saxena-Easo fuzzy time series doesn’t need stationarity like conventional forecasting method, capable of dealing with the value of time series which are linguistic and has the advantage of reducing the calculation, time and simplifying the calculation process. Generally it’s focus on percentage change as the universe discourse, interval partition and defuzzification. The result indicate that between the actual data and the forecast data are close enough with Root Mean Square Error (RMSE)= 1.5289.
    URI
    http://repository.unej.ac.id/handle/123456789/102047
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    • LSP-Jurnal Ilmiah Dosen [7411]

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    Indonesia DSpace Group :

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