BibTex Citation Data :
@article{J.Gauss10134, author = {Dita Ruliana and Sugito Sugito and Dwi Ispriyanti}, title = {PERAMALAN INDEKS HARGA KONSUMEN MENGGUNAKAN MODEL INTERVENSI FUNGSI STEP}, journal = {Jurnal Gaussian}, volume = {4}, number = {4}, year = {2015}, keywords = {consumer price index, stationery, ARIMA, step function intervention analysis, forecasting}, abstract = { Intervention model is a model for time series data in which practically there is an extreme fluctuation, whether it’s anupward or downward fluctuation. Consumer price index is one of economic data which plot has a fluctuation, the data that will being used for analyze is consumer price index of Indonesia in January 2009 until March 2015, on data detectable downward fluctuation significantly on January 2014 (T=61). Intervention in data was occurred in long time period (T=61 until T=75), so the model of intervention’s assumption is step function. Based on the result and analysis, the obtaining best model of intervention is ARIMA (2,1,3) with intervention order b=0 s=15 and r=0 which later on being used for predicting Indonesian consumer price index in six periods ahead. Keywords : consumer price index, stationery, ARIMA, step function intervention analysis, forecasting }, issn = {2339-2541}, pages = {795--804} doi = {10.14710/j.gauss.4.4.795-804}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/10134} }
Refworks Citation Data :
Intervention model is a model for time series data in which practically there is an extreme fluctuation, whether it’s anupward or downward fluctuation. Consumer price index is one of economic data which plot has a fluctuation, the data that will being used for analyze is consumer price index of Indonesia in January 2009 until March 2015, on data detectable downward fluctuation significantly on January 2014 (T=61). Intervention in data was occurred in long time period (T=61 until T=75), so the model of intervention’s assumption is step function. Based on the result and analysis, the obtaining best model of intervention is ARIMA (2,1,3) with intervention order b=0 s=15 and r=0 which later on being used for predicting Indonesian consumer price index in six periods ahead.
Keywords : consumer price index, stationery, ARIMA, step function intervention analysis, forecasting
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