Inferensi
Vol 6, No 1 (2023)

Prediksi Harga Ekspor Non Migas di Indonesia Berdasarkan Metode Estimator Deret Fourier dan Support Vector Regression

Chaerobby Fakhri Fauzaan Purwoko (Universitas Airlangga)
Sediono Sediono (Universitas Airlangga)
Toha Saifudin (Universitas Airlangga)
M Fariz Fadillah Mardianto (Universitas Airlangga)



Article Info

Publish Date
29 Mar 2023

Abstract

Economic growth is one of the indicators in the Sustainable Development Goals (SDGs) on increasing economic activity.  One of the activities that supports the running of the economy is trade between countries, such as exports.  In Indonesia, non-oil and gas exports have played an important role in total exports in recent years, including coal exports being the main export.  Therefore, price predictions for Indonesia's non-oil and gas exports are very important as material for evaluating policies to encourage economic growth.  This is the main focus of this research.  In this study, non-oil and gas export price forecasts are made taking into account current issues such as the COVID-19 pandemic and the Russia-Ukraine war.  The accuracy of the model obtained from the Fourier series estimator and Support Vector Regression (SVR) is investigated by comparing the Mean Absolute Percentage Error (MAPE) value to predict Indonesia's non-oil and gas export prices.  The results of the study show that the COVID-19 pandemic and the Russia-Ukraine war have had a significant impact on non-oil and gas export prices. The SVR model with the Radial Basis Function (RBF) kernel shows better accuracy than the Fourier series estimator model of the cos sin function, with MAPE values of 9.29 and 15.26% for each test data, respectively.  Therefore, this study is expected to be the basis for formulating policies related to regulating non-oil and gas export processes to support economic growth in Indonesia.

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Journal Info

Abbrev

inferensi

Publisher

Subject

Computer Science & IT Decision Sciences, Operations Research & Management Engineering Mathematics Social Sciences

Description

The aim of Inferensi is to publish original articles concerning statistical theories and novel applications in diverse research fields related to statistics and data science. The objective of papers should be to contribute to the understanding of the statistical methodology and/or to develop and ...