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All Journal Indonesian Journal on Computing (Indo-JC)
Ni Luh Ketut Dwi Murniati
School of Computing, Telkom University
Computer Science & IT

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Implemetasi Model Autoregressive (AR) Dan Autoregressive Conditional Heteroskedasticity (ARCH) Untuk Memprediksi Harga Emas Ni Luh Ketut Dwi Murniati; Indwiarti Indwiarti; Aniq Atiqi Rohmawati
Indonesia Journal on Computing (Indo-JC) Vol. 3 No. 2 (2018): September, 2018
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/INDOJC.2018.3.2.225

Abstract

Gold is a one of  high selling value items in the market, and it  can be used as an investment item. The price of gold in the market tends to be stable and not undergoing too significant changes which makes gold be a very valuable item. The aim of this research is to predict gold price using AR (1) and ARCH (1) model which are the part of time series methods. The data of gold price is obtained from ANTAM's daily historical website from 2007 - 2017. Here, the basic information about data is given by using descriptive statistic and the estimation of parameters in each model is condacted by using Maximum Likelihood Estimation (MLE). To evaluate the model, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) are used. In this research, the estimated model of AR (1) and ARCH (1) given as X_t = -0.012X_{t-1}+epsion_t and X_t = epsilon_t sqrt{0.000053+0.011958X^2_{t-1}} respectively. Moreover, the result of MAE and RMSE using AR (1) model are 0.0261 and 0.0342 respectively, meanwhile for ARCH (1) model  are 0.0170 and 0.0251 respectively.
Co-Authors Aniq Atiqi Rohmawati Indwiarti