EKSAKTA: Journal of Sciences and Data Analysis
VOLUME 5, ISSUE 1, April 2024

Forecasting of Export Value in Indonesia Using Top-Down Hierarchical Time Series Based on Historical Proportion

Inas Rafidah (Unknown)
Kartikasari, Mujiati Dwi (Unknown)



Article Info

Publish Date
27 Jan 2024

Abstract

Export is a trading activity carried out between countries by bringing or sending goods originating from within the country to foreign countries with the aim of selling or marketing them. Exports as a source of state revenue are needed for the economy because exports can make a major contribution to economic stability and growth. Export values that experience a decrease or increase in the future need to be considered. For this reason, the purpose of this study is to forecast the value of exports in Indonesia for the coming period. Export value data is treated as hierarchical time series data. The top-down method is applied based on historical proportions, so only the total series of export values needs to be modeled. This study implements Autoregressive Integrated Moving Average (ARIMA) to model the total series of export values. The performance of the method is evaluated based on the out-of-sample mean absolute percentage error (MAPE). The results show that the MAPE for out-of-sample is 9.91%. These results indicate that the performance of the method for forecasting export values in Indonesia is highly accurate.

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Journal Info

Abbrev

eksakta

Publisher

Subject

Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology

Description

Ekstakta is an interdisciplinary journal with the scope of mathematics and natural sciences that is published by Fakultas MIPA Universitas Islam Indonesia. All submitted papers should describe original, innovatory research, and modelling research indicating their basic idea for potential ...