BibTex Citation Data :
@article{J.Gauss35528, author = {ARYA YAHYA}, title = {PERAMALAN INDEKS HARGA KONSUMEN INDONESIA MENGGUNAKAN METODE SEASONAL-ARIMA (SARIMA)}, journal = {Jurnal Gaussian}, volume = {11}, number = {2}, year = {2022}, keywords = {SARIMA, IHK, Seasonal, Indonesia}, abstract = { The pattern of changes in the Consumer Price Index (CPI) is very important to observe from time to time because it is closely related to economic indicators such as the amount of money in circulation, exchange rates, interest rates, and other economic indicators. This study aims to form a model and predict the Indonesian Consumer Price Index using the SARIMA method. The data used in modeling are monthly CPI data for the period January 2012 to February 2022. The best model for predicting Indonesia's CPI is the SARIMA (0,1,1)(0,1,1) 12 model. This study examines the CPI value in January and February 2022 which is not included in the estimation model, the estimation results (108,08 and 108,20) are very close to the actual CPI value issued by the Central Statistics Agency. }, issn = {2339-2541}, pages = {313--322} doi = {10.14710/j.gauss.v11i2.35528}, url = {https://ejournal3.undip.ac.id/index.php/gaussian/article/view/35528} }
Refworks Citation Data :
The pattern of changes in the Consumer Price Index (CPI) is very important to observe from time to time because it is closely related to economic indicators such as the amount of money in circulation, exchange rates, interest rates, and other economic indicators. This study aims to form a model and predict the Indonesian Consumer Price Index using the SARIMA method. The data used in modeling are monthly CPI data for the period January 2012 to February 2022. The best model for predicting Indonesia's CPI is the SARIMA (0,1,1)(0,1,1)12 model. This study examines the CPI value in January and February 2022 which is not included in the estimation model, the estimation results (108,08 and 108,20) are very close to the actual CPI value issued by the Central Statistics Agency.
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