Abstrak 
Generalized Space Time Autoregressive Integrated Moving Average (GSTARIMA) Model to Forecast Cocoa Export Volume
Lum’atul Qomariyah, Toni Toharudin, Soemartini
Universitas Padjadjaran, Proceeding of The 2nd International Conference on Applied Statistics 2016 ISSN : 2579-4361
Bahasa Inggris
Universitas Padjadjaran, Proceeding of The 2nd International Conference on Applied Statistics 2016 ISSN : 2579-4361
cocoa, GSTAR, GSTARIMA, Space Time
Generalized Space Time Autoregressive (GSTAR) is one of time series model used to forecast the data consisting the element of space and time. This model is limited to the stationary and non-seasonal data. Generalized Space Time Autoregressive Integrated Moving Average (GSTARIMA) is GSTAR development model that accommodates the non-stationary and seasonal data. In this research, the model was applied to the monthly cocoa export volume data from DKI Jakarta, Jawa Tengah and Jawa Timur in the last 8 years. Indonesian cocoa export volume in the third position in the world trade, after Ivory Coast and Ghana. Identification of the AR and MA are using the minimum value of AIC. Spatial order is chosen in first order because all of the provinces in this research are located in one island. From the two spatial weight matrix, which distance inverse and normalized cross-correlation between locations to the corresponding lag, we have the minimum MSE value to the data is distance inverse.