Pemodelan Harga Beras di Pulau Sumatera dengan Menggunakan Model Generalized Space Time ARIMA
Author(s) -
Dwi Yulianti,
I Made Sumertajaya,
Itasia Dina Sulvianti
Publication year - 2018
Publication title -
xplore journal of statistics
Language(s) - English
Resource type - Journals
eISSN - 2655-2744
pISSN - 2302-5751
DOI - 10.29244/xplore.v2i2.105
Subject(s) - autoregressive integrated moving average , contiguity , autoregressive model , time series , mathematics , series (stratigraphy) , statistics , geography , econometrics , computer science , paleontology , biology , operating system
Generalized space time autoregressive integrated moving average (GSTARIMA) model is a time series model of multiple variables with spatial and time linkages (space time). GSTARIMA model is an extension of the space time autoregressive integrated moving average (STARIMA) model with the assumption that each location has unique model parameters, thus GSTARIMA model is more flexible than STARIMA model. The purposes of this research are to determine the best model and predict the time series data of rice price on all provincial capitals of Sumatra island using GSTARIMA model. This research used weekly data of rice price on all provincial capitals of Sumatra island from January 2010 to December 2017. The spatial weights used in this research are the inverse distance and queen contiguity. The modeling result shows that the best model is GSTARIMA (1,1,0) with queen contiguity weighted matrix and has the smallest MAPE value of 1.17817 %.
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