PERAMALAN NILAI EKSPOR MIGAS DAN NON-MIGAS DI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE FRACTIONAL INTEGRATED MOVING AVERAGE

dc.contributor.authorRismawati, Yulia
dc.contributor.supervisorEfendi, Rustam
dc.date.accessioned2023-05-23T08:15:23Z
dc.date.available2023-05-23T08:15:23Z
dc.date.issued2023-02
dc.description.abstractThe autoregressive fractional integrated moving average model is a development of the Autoregressive integrated moving average model which is used for data containing elements of long memory. This model uses differencing decimal numbers. In this study, the ARFIMA model is used for modeling data on the value of oil and gas and non-oil exports in Indonesia with a monthly period from 2000 to 2020 and then forecasting for the next 12 periods. The first step is to identify long memory using hurst statistics. The result of the estimation of parameter d using the Rescaled Range Statistics (R/S) method, the value of d=0.4 is obtained. The best ARFIMA model obtained is ARFIMA (2, d, 1) with d=0.4 having an AIC value of 3457.114 and a MAPE value of 16.5%. This indicates a good level of forecasting abilityen_US
dc.description.sponsorshipFakultas Matematika dan Ilmu Pengetahuan Alam Universitas Riauen_US
dc.identifier.citationPerpustakaanen_US
dc.identifier.otherElfitra
dc.identifier.urihttps://repository.unri.ac.id/handle/123456789/11000
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectOil and gas and non-oil and gas exportsen_US
dc.subjectlong memoryen_US
dc.subjectARFIMAen_US
dc.subjectRescaled Range Statisticsen_US
dc.subjectHursten_US
dc.titlePERAMALAN NILAI EKSPOR MIGAS DAN NON-MIGAS DI INDONESIA MENGGUNAKAN MODEL AUTOREGRESSIVE FRACTIONAL INTEGRATED MOVING AVERAGEen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
YULIA RISMAWATI _compressed.pdf
Size:
285.13 KB
Format:
Unknown data format
Description:
artikel
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:

Collections