Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal International Journal of Computing Science and Applied Mathematics
Hadijati, Mustika
Universitas Mataram
Computer Science & IT Education Mathematics

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Hybrid ARIMA Modeling with Stochastic Volatility for Forecasting the Value of Non-Oil and Gas Exports in Indonesia Suryatin, Evatia; Hadijati, Mustika; Widya Baskara, Zulhan
(IJCSAM) International Journal of Computing Science and Applied Mathematics Vol 10, No 1 (2024)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24775401.v10i1.20265

Abstract

Export activities consist of oil and gas exports and non-oil and gas exports. Non-oil and gas exports are one of the sectors that provide the largest foreign exchange contribution to Indonesia, and the movement of non-oil and gas export values has an impact on economic growth. Therefore, the purpose of this research is to create a model used to predict future non-oil and gas export values. One mathematical model that can be to predict Indonesia’s non-oil and gas export values is the combination of the ARIMA model and the stochastic volatility model, also known as Hybrid ARIMA with stochastic volatility. The Hybrid ARIMA with stochastic volatility modeling has advantages in creating models for data with high volatility and is capable of combining linear patterned data and nonlinear patterned data. In this study, the best ARIMA (1,1,1) model was obtained with a MAPE value of 13.2082%. From the residuals of the ARIMA (1,1,1) model, there were signs of heteroscedasticity, so the GARCH model with the best GARCH (0,1) model was used. In the GARCH (0,1) model, it was found that there was an asymmetric influence, so the EGARCH and GJR-GARCH models were used. The comparison of EGARCH and GJR-GARCH models was carried out to address the asymmetric residual data pattern. Based on the research results, the best model used for prediction is the hybrid ARIMA (1,1,1) with EGARCH (1,1) model, with a MAPE value of 9.35158%.
Co-Authors Suryatin, Evatia Widya Baskara, Zulhan