A Comparison of Univariate ARIMA and Multivariate to Estimate Absorption Pattern in Stronsium Tittanate Dop Variation

Authors

  • Dina Oktasari  Department of Statistic, Bogor Agriculture University, Bogor, Indonesia
  • Muhammad Nur Aidi  Department of Statistic, Bogor Agriculture University, Bogor, Indonesia
  • I Made Sumertajaya  Department of Statistic, Bogor Agriculture University, Bogor, Indonesia

Keywords:

ARIMA, VARIMA, GSTARIMA, modeling, forecasting.

Abstract

ARIMA, VARIMA, and GSTARIMA are the models used to model the observation series and variable dop containing spatial dependence between its dop. More complex models do not guarantee the forecast result will be more accurate. Therefore, the aims of this study are to model and assess the accuracy of forecasting of the ARIMA, VARIMA, and GSTARIMA using space weight is normalization of cross correlation. It was applied to the absorption pattern in stronsium tittanate with variation of dop. Based on this study, the fitted model used were ARIMA, VARI, and GSTARI modeling using normalization of cross correlation with the order of observation series AR(2). In addition, the ARIMA model more accurate to forecast the absorption pattern in stronsium tittanate with variation of dop than VARI and GSTARI model.

References

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-08-30

Issue

Volume 4, Issue 9, July-August-2018

Section

Research Articles

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Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dina Oktasari, Muhammad Nur Aidi, I Made Sumertajaya "A Comparison of Univariate ARIMA and Multivariate to Estimate Absorption Pattern in Stronsium Tittanate Dop Variation" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 9, pp.356-360, July-August-2018.