BibTex Citation Data :
@article{J.Gauss8081, author = {Kiki Azriati and Abdul Hoyyi and Moch. Mukid}, title = {VERIFIKASI MODEL ARIMA MUSIMAN MENGGUNAKAN PETA KENDALI MOVING RANGE (Studi Kasus : Kecepatan Rata-rata Angin di Badan Meteorologi Klimatologi dan Geofisika Stasiun Meteorologi Maritim Semarang)}, journal = {Jurnal Gaussian}, volume = {3}, number = {4}, year = {2014}, keywords = {}, abstract = { Forecasting method Box-Jenkins ARIMA (Autoregressive Integrated Moving Average) is a forecasting method that can provide a more accurate forecasting results. To verify the model obtained using the one Moving Range Chart. The control charts are used to determine the change in the pattern of file seen from the residual value (the difference between the actual file and the file forecasting). File used in this study the average wind speed in the Tanjung Emas harbor during January 2008 to December 2013. The best of Seasonal ARIMA model is ARIMA (0,0,1) (0,0,1) 12. The results of the verification using the Moving Range Control Chart on the model showed that all residual values are within control limits to the length of the shortest interval, means of verification results show that the model is a good model used for forecasting future periods. Forecasting is generated during the period of the next 15 shows the seasonal pattern. This is shown in the figure forecast 2014 average wind speeds are highest in January, as well as forecasting the 2015 figures the average speed of the highest winds also occurred in January. Forecasting results reflect past file, because the actual file used also showed a seasonal pattern with the same seasonal period is annual, where the numbers mean wind speeds are highest in January. Keywords : Seasonal ARIMA, Moving Range Control Chart, Mean wind speeds. }, issn = {2339-2541}, pages = {701--710} doi = {10.14710/j.gauss.3.4.701-710}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/8081} }
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Forecasting method Box-Jenkins ARIMA (Autoregressive Integrated Moving Average) is a forecasting method that can provide a more accurate forecasting results. To verify the model obtained using the one Moving Range Chart. The control charts are used to determine the change in the pattern of file seen from the residual value (the difference between the actual file and the file forecasting). File used in this study the average wind speed in the Tanjung Emas harbor during January 2008 to December 2013. The best of Seasonal ARIMA model is ARIMA (0,0,1) (0,0,1) 12. The results of the verification using the Moving Range Control Chart on the model showed that all residual values are within control limits to the length of the shortest interval, means of verification results show that the model is a good model used for forecasting future periods. Forecasting is generated during the period of the next 15 shows the seasonal pattern. This is shown in the figure forecast 2014 average wind speeds are highest in January, as well as forecasting the 2015 figures the average speed of the highest winds also occurred in January. Forecasting results reflect past file, because the actual file used also showed a seasonal pattern with the same seasonal period is annual, where the numbers mean wind speeds are highest in January.
Keywords : Seasonal ARIMA, Moving Range Control Chart, Mean wind speeds.
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