ESTIMATOR POLINOMIAL LOKAL UNTUK PEMODELAN HARGA EMAS DI INDONESIA MENGGUNAKAN REGRESI NONPARAMETRIK
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Date
2022-05
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Elfitra
Abstract
This 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.
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Keywords
Nonparametric regression, local polynomial estimator, Weighted Least Square, Generalized Cross Validation, Mean Absolute Percentage Error
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