Hierarchical time series bottom-up approach for forecast the export value in Central Java

D. A. Mahkya, B. S. Ulama, Suhartono

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)


The purpose of this study is Getting the best modeling and predicting the export value of Central Java using a Hierarchical Time Series. The export value is one variable injection in the economy of a country, meaning that if the export value of the country increases, the country's economy will increase even more. Therefore, it is necessary appropriate modeling to predict the export value especially in Central Java. Export Value in Central Java are grouped into 21 commodities with each commodity has a different pattern. One approach that can be used time series is a hierarchical approach. Hierarchical Time Series is used Buttom-up. To Forecast the individual series at all levels using Autoregressive Integrated Moving Average (ARIMA), Radial Basis Function Neural Network (RBFNN), and Hybrid ARIMA-RBFNN. For the selection of the best models used Symmetric Mean Absolute Percentage Error (sMAPE). Results of the analysis showed that for the Export Value of Central Java, Bottom-up approach with Hybrid ARIMA-RBFNN modeling can be used for long-term predictions. As for the short and medium-term predictions, it can be used a bottom-up approach RBFNN modeling. Overall bottom-up approach with RBFNN modeling give the best result.

Original languageEnglish
Article number012033
JournalJournal of Physics: Conference Series
Issue number1
Publication statusPublished - 28 Oct 2017
EventAsian Mathematical Conference 2016, AMC 2016 - Nusa Dua, Bali, Indonesia
Duration: 25 Jul 201629 Jul 2016


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