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dc.contributor.authorAhmar, Ansari Saleh
dc.contributor.authorGuritno, Suryo
dc.contributor.authorAbdurakhman, Abdurakhman
dc.contributor.authorRahman, Abdul
dc.contributor.authorAwi, Awi
dc.contributor.authorAlimuddin, Alimuddin
dc.contributor.authorMinggi, Ilham
dc.contributor.authorTiro, M Arif
dc.contributor.authorAidid, M Kasim
dc.contributor.authorAnnas, Suwardi
dc.contributor.authorSutiksno, Dian Utami
dc.contributor.authorAhmar, Dewi S
dc.contributor.authorAhmar, Kurniawan H
dc.contributor.authorAhmar, A Abqary
dc.contributor.authorZaki, Ahmad
dc.contributor.authorAbdullah, Dahlan
dc.contributor.authorRahim, Robbi
dc.contributor.authorNurdiyanto, Heri
dc.contributor.authorHidayat, Rahmat
dc.contributor.authorNapitupulu, Darmawan
dc.contributor.authorSimarmata, Janner
dc.contributor.authorKurniasih, Nuning
dc.contributor.authorAbdillah, Leon Andretti
dc.contributor.authorPranolo, Andri
dc.contributor.authorHaviluddin, Haviluddin
dc.contributor.authorAlbra, Wahyudin
dc.contributor.authorArifin, A Nurani M
dc.date.accessioned2020-01-17T02:04:13Z
dc.date.available2020-01-17T02:04:13Z
dc.date.issued2018-02-22
dc.identifier.issn1742-6596
dc.identifier.urihttp://repository.unmul.ac.id/handle/123456789/3599
dc.description.abstractThe aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. In the simulation data is obtained that the data contained AO initial models are ARIMA (2,0,0) with MSE = 36,780, after the detection and correction of data obtained by the iteration of the model ARIMA (2,0,0) with the coefficients obtained from the regression Zt= 0,106 + 0, 204Zt-1 + 0, 401Zt-2 - 329X1(t) + 115X2(t) + 35,9X3(t) and MSE = 19,365. This shows that there is an improvement of forecasting error rate data.en_US
dc.language.isoenen_US
dc.publisherIOP Conf. Series: Journal of Physics: Conf. Series 954en_US
dc.subjectforecasting; ARIMA-AO; Outlier; MSEen_US
dc.titleModeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)en_US
dc.typeArticleen_US
dc.identifier.nidn0028057303
dc.identifier.kodeprodi55281


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