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Ronny Gusnadi
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PEMODELAN GENERALIZED SPACE TIME AUTOREGRESSIVE (GSTAR) SEASONAL PADA DATA JUMLAH WISATAWAN MANCANEGARA EMPAT KABUPATEN/KOTA DI JAWA TENGAH Ronny Gusnadi; Rita Rahmawati; Alan Prahutama
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (763.365 KB) | DOI: 10.14710/j.gauss.v4i4.10237

Abstract

In many applications, several time series data are recorded simultaneously at a number of locations. Time series data from nearby locations often to be related by spatial and time. This data is called spatial time series data. Generalized Space Time Autoregressive (GSTAR) model is one of space time models used to modeling and forecasting spatial time series data. This study applied GTSAR model  to modeling number of international tourist four locations in Magelang Regency, Surakarta City, Wonosobo Regency, and Karanganyar Regency. Based on the smallest RMSE mean of forecasting result, the best model chosen by this study is GSTAR(11)-I(1)12 with the inverse distance weighted. Based on GSTAR(11)-I(1)12 with the inverse distance weighted, the relationship between the location shown on International tourist arrivals Surakarta City influenced by the International tourist in other regencies. Keywords: GSTAR, RMSE, International Tourist
Co-Authors Alan Prahutama Rita Rahmawati