ESTIMATOR POLINOMIAL LOKAL UNTUK PEMODELAN HARGA EMAS DI INDONESIA MENGGUNAKAN REGRESI NONPARAMETRIK

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dc.contributor.authorDani, Rudy Rama
dc.contributor.supervisorEfendi, Rustam
dc.date.accessioned2022-09-19T08:36:34Z
dc.date.available2022-09-19T08:36:34Z
dc.date.issued2022-05
dc.description.abstractThis paper discusses about the nonparametric regression model based on local polynomial estimators on gold prices in Indonesia. Local polynomial estimators can be obtained by minimizing Weighted Least Square (WLS). Optimal bandwidth can be obtained using the Generalized Cross Validation (GCV) method. Furthermore this methods are applied to nonparametric regression models based on local polynomial estimators in the case of gold prices in Indonesia. Gold price modeling in Indonesia using local polynomial regression with Gaussian kernel function obtained optimal bandwidth of 10. The model produces a minimum GCV score of 854882843 with the optimum order of the local polynomial is order 4. The goodness of fit model used is the Mean Absolute Percentage Error (MAPE) with MAPE 6.182%, that is smaller them 10%. Then local polynomial regression model order 4 for gold price is very accurate.en_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/123456789/10681
dc.language.isoenen_US
dc.publisherElfitraen_US
dc.subjectNonparametric regressionen_US
dc.subjectlocal polynomial estimatoren_US
dc.subjectWeighted Least Squareen_US
dc.subjectGeneralized Cross Validationen_US
dc.subjectMean Absolute Percentage Erroren_US
dc.titleESTIMATOR POLINOMIAL LOKAL UNTUK PEMODELAN HARGA EMAS DI INDONESIA MENGGUNAKAN REGRESI NONPARAMETRIKen_US
dc.typeArticleen_US

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