Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal Panrannuangku Jurnal Pengabdian Masyarakat Jurnal Hasil-Hasil Pengabdian dan Pemberdayaan Masyarakat (JHP2M) Journal of Mathematics, Computation and Statistics (JMATHCOS)
Nyulle, Rusdianto
Unknown Affiliation
Humanities Education Engineering Health Professions Library & Information Science Mathematics Social Sciences Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Mathematics, Computation and Statistics (JMATHCOS)

 1 
APPLICATION OF GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY (GARCH) MODEL IN FORECASTING THE MARKET PRICE OF NICKEL IN INDONESIA Sidjara, Sahlan; Sanusi, Wahidah; Nyulle, Rusdianto
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9798

Abstract

Indonesia is one of the largest nickel exporting countries in the world, with the increasing demand for electric vehicles making nickel a target for producers. The increase in nickel demand makes it necessary to increase the observation of nickel prices to maintain the sustainability of the mining industry and economic growth. The purpose of this study is to forecast the price of Indonesia's nickel market using the GARCH method. The GARCH method is one of the methods used in time series data modeling that identifies heteroscedatic effects. The steps taken are to analyze the training data, check the stationery, estimate the parameters, and test the diagnostic model, then the best ARIMA model is selected based on the smallest AIC value, namely ARIMA (0,1,1). The residual values of the best ARIMA models are then used to determine the GARCH model. The best GARCH model obtained is GARCH (0.1) with an AIC value of 19.04061. Furthermore, forecasting was carried out using the GARCH model (0.1) and comparing the forecast results with the testing data to obtain MAPE values. The MAPE value obtained is 17.67014 % which shows that the GARCH model (0.1) has good forecasting accuracy, so this model is quite feasible to be used in forecasting the price of Indonesia's nickel market.
Co-Authors Abdul Rahman Ahmad Zaki Irwan Irwan Ja'faruddin, Ja'faruddin Ja’faruddin, Ja'faruddin Nurdin Arsyad, Nurdin Sidjara, Sahlan Utary, Utary Wahidah Sanusi