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Natanael, Dimas Kevin
Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Muham

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PREDIKSI HARGA MINYAK DUNIA DENGAN METODE AUTOREGRESSIVE FRACTIONALLY INTEGRATED MOVING AVERAGE (ARFIMA) Natanael, Dimas Kevin; Safitri, Diah; Suparti, Suparti
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 6, No 1 (2018): Jurnal Statistika
Publisher : Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Muham

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Abstract

Autoregressive Fractionally Integrated Moving Average (ARFIMA) model is a development of the ARIMA model. The advantage of the ARFIMA method is the non-integer differentiation value so that it can overcome long memory effect that cannot be solve with the usual ARIMA method. Non-integer differential values can be estimated with a binomialexpansion approach which is an infinite weighted sum of past values to solve the long memory effect that arises. Some of the advantages of using the ARFIMA model iscapable of modeling high changes in the long term (long term persistence), be able to explain longterm and short-termcorrelation structures at the same time, to provide models with simple parameters (parsimony) for data with memory long term and short term. Data of world oil price contain long memory effect, then used ARFIMA method to get the best model.The best model obtained is the ARMA([1,7]; 0) model with the differentialvalue is 0,48937, then the model can be written into ARFIMA ([1,7]; d;1).The best model chosen has an MSE value of 0,44 and a MAPE value of 3,32%. Keywords : Sea Passengers, ARIMA Box-Jenkins, Calendar Variation, ARIMAX