?url_ver=Z39.88-2004&rft_id=1817031031&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=PENERAPAN+METODE+AUTOREGRESSIVE+FRACTIONALLY%0D%0AINTEGRATED+MOVING+AVERAGE+(ARFIMA)+PADA+DATA%0D%0ANILAI+EKSPOR+MIGAS&rft.creator=ANIISAH%2C++NURFAIZAH+SUSANTO&rft.subject=500+ilmu+pengetahuan+alam+dan+matematika&rft.subject=510+Matematika&rft.description=The+ARFIMA+model+is+a+development+of+the+ARIMA+model+which+has+the%0D%0Aadvantage+of+being+able+to+explain+short+and+long+term+time+series.+The+ARFIMA%0D%0Amodel+was+first+introduced+by+Grager+(1980)+which+was+then+continued+by%0D%0AHosking+(1981)+regarding+the+study+of+the+properties+of+long+memory.+This+study%0D%0Aaims+to+determine+the+best+model+by+comparing+the+Akaike+Information+Criterion%0D%0A(AIC)+values+and+measuring+the+estimated+value+in+the+form+of+a+percentage+of+the%0D%0Aaverage+error+of+the+model+obtained.+The+data+used+in+this+study+is+secondary+data%0D%0Aobtained+from+the+Central+Bureau+of+Statistics+regarding+the+Value+of+Oil+and+Gas%0D%0AExports+for+the+period+January+2012+to+December+2021.+Based+on+the+research+that%0D%0Ahas+been+conducted+it+can+be+concluded+that+the+model+chosen+for+forecasting+Oil%0D%0Aand+Gas+Exports%2C+namely+ARFIMA(2%3B0.045%3B+0)+with+an+AIC+value+of+1316.237%0D%0Aand+a+model+accuracy+value+of+1.39%25.%0D%0AKeywords%3A+ARFIMA%2C+Long+Memory%2C+Oil+and+Gas+Export+Value%2C+AIC%2C+MAPE.%0D%0A%0D%0A%0D%0AModel+ARFIMA+merupakan+pengembangan+dari+model+ARIMA+yang+memiliki%0D%0Akelebihan+dapat+menjelaskan+runtun+waktu+jangka+pendek+maupun+panjang.%0D%0AModel+ARFIMA+pertama+kali+diperkenalkan+oleh+Grager+(1980)+yang+kemudian%0D%0Adilanjutkan+oleh+Hosking+(1981)+mengenai+pengkajian+terhadap+sifat-sifat+long%0D%0Amemory.+Penelitian+ini+bertujuan+untuk+menentukan+model+terbaik+dengan%0D%0Amembandingkan+nilai+Akaike+Information+Criterion+(AIC)+dan+mengukur+nilai%0D%0Adugaan+dalam+bentuk+persentase+dari+rata-rata+galat+model+yang+didapatkan.+Data%0D%0Ayang+digunakan+dalam+penelitian+ini+ialah+data+sekunder+yang+diperoleh+dari%0D%0ABadan+Pusat+Statistik+tentang+Nilai+Ekspor+Migas+periode+Januari+2012+sampai%0D%0Adengan+Desember+2021.+Berdasarkan+penelitian+yang+telah+dilakukan+dapat%0D%0Adisimpulkan+bahwa+model+yang+terpilih+untuk+prakiraan+Ekspor+Migas%2C+yaitu%0D%0AARFIMA(2%3B0%2C045%3B0)+dengan+nilai+AIC+sebesar+1316%2C237+dan+nilai+keakuratan%0D%0Amodel+sebesar+1%2C39%25.%0D%0AKata+Kunci%3A+ARFIMA%2C+Long+Memory%2C+Nilai+Ekspor+Migas%2C+AIC%2C+MAPE.%0D%0A&rft.publisher=FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM&rft.date=2023-01-04&rft.type=Skripsi&rft.type=NonPeerReviewed&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F68665%2F1%2F1.%2520ABSTRAK.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F68665%2F2%2F2.%2520SKRIPSI%2520FULL.pdf&rft.format=text&rft.identifier=http%3A%2F%2Fdigilib.unila.ac.id%2F68665%2F3%2F3.%2520SKRIPSI%2520TANPA%2520BAB%2520PEMBAHASAN.pdf&rft.identifier=++ANIISAH%2C+NURFAIZAH+SUSANTO++(2023)+PENERAPAN+METODE+AUTOREGRESSIVE+FRACTIONALLY+INTEGRATED+MOVING+AVERAGE+(ARFIMA)+PADA+DATA+NILAI+EKSPOR+MIGAS.++FAKULTAS+MATEMATIKA+DAN+ILMU+PENGETAHUAN+ALAM%2C+UNIVERSITAS+LAMPUNG.+++++&rft.relation=http%3A%2F%2Fdigilib.unila.ac.id%2F68665%2F