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All Journal Jurnal Ilmu Dasar Jurnal Sains dan Seni ITS IPTEK Journal of Proceedings Series
Suhartono Suhartono
Institut Teknologi Sepuluh Nopember, Surabaya
Arts Humanities Computer Science & IT Control & Systems Engineering Mathematics

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Simulation of Generalized Space-Time Autoregressive with Exogenous Variables Model with X Variable of Type Metric Reza Mubarak; Suhartono Suhartono
IPTEK Journal of Proceedings Series No 1 (2015): 1st International Seminar on Science and Technology (ISST) 2015
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (331.186 KB) | DOI: 10.12962/j23546026.y2015i1.1170

Abstract

One of the models time series which also involves spatial aspects (spatio-temporal) is Generalized Space Time Autoregressive (GSTAR). Until now, GSTAR modelling don’t involve metric-type, which is called GSTARX. Parameter estimation for spatio temporal modeling is still limited by using Ordinary Least Square (OLS) which is less efficient because the residuals are correlated. Generalized Least Square (GLS) is one of the alternative methods for parameter estimation residuals are correlated. In this study would like to looking at the efficiency of GLS estimation method is compared with OLS to correlated data in GSTARX model. Simulation results show that the estimation GLS method is more efficient than using OLS if residual correlated.
Seasonal Multivariat Time Series Forecasting On Tourism Data by Using Var-Gstar Model Dhoriva Urwatul Wutsqa; suhartono Suhartono
Jurnal ILMU DASAR Vol 11 No 1 (2010)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (203.061 KB)

Abstract

This research intends to study a new approach VAR-GSTAR (Vector Autoregressive-General Space-Time Autoregressive) model for forecasting seasonal multivariate time series. The parameters of the model are estimated by Least Squares method. In this research, we also derive the asymptotic properties of the parameter estimator, which yield the consistency and multivariate normal asymptotes distribution. Based on those properties, we build the procedure for finding the best model in seasonal multivariate time series, and then apply it on the number of foreign tourists in Yogyakarta and Bali data. The result from VAR-GSTAR model is compared with the result from the standard multivariate time series. The comparison result demonstrates that the procedure of VARMA model can not carry out the seasonal lags on the order of the model. This problem can be handled by the VAR-GSTAR model. The interpretation of VAR-GSTAR model is more realistic than that of VARMA model, i.e. the number of foreign tourists in Yogyakarta depends on that in Bali, but not the opposite, whereas VARMA model yields the opposite result. Additionally, the result of forecast accuracy comparison on tourism data in Yogyakarta and Bali shows that VAR-GSTAR model give better forecast than VARMA model. 
Co-Authors Agus Suharsono Andria Prima Ditago Clara Agustin Stephani Dhoriva Urwatul Wutsqa Eva Laylatus Fakhrul Azizi Indillah Hidayatul Khusna Indah Kurnia Putri Indana La Zulfa Nayla Nayla Ma’rufah Ma’rufah Noorgam Ika Rachmawati Retno Dyah Handini Reza Mubarak Santi Puteri Rahayu Setiawan Setiawan