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All Journal Signifikan : Jurnal Ilmu Ekonomi Media Statistika Jurnal Sains dan Seni ITS IPTEK Journal of Proceedings Series International Journal of Advances in Intelligent Informatics Jurnal Ekonomi Pembangunan: Kajian Masalah Ekonomi dan Pembangunan Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Jurnal Aplikasi Statistika & Komputasi Statistik Inferensi Madaniya Proceeding ISETH (International Summit on Science, Technology, and Humanity) Bulletin of Applied Mathematics and Mathematics Education Aceh International Journal of Science and Technology Eduvest - Journal of Universal Studies
Dedy Dwi Prastyo
Department Of Statistics, Institut Teknologi Sepuluh Nopember
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Journal : Jurnal Aplikasi Statistika

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Modeling Multi-Output Back-Propagation DNN for Forecasting Indonesian Export-Import Maharsi, Rengganis Woro; Saputra, Wisnowan Hendy; Roosyidah, Nila Ayu Nur; Prastyo, Dedy Dwi; Rahayu, Santi Puteri
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 16 No 1 (2024): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v16i1.459

Abstract

Introduction/Main Objectives: International trade through the mechanisms of exports and imports plays a significant role in the Indonesian economy, making the timely availability of export and import value data crucial. Background Problems: Export and import values are influenced by inflation and exchange rate factors. Novelty: This study identifies two categories of variables, namely output (export value and import value) and input (inflation rate and the exchange rate of the Rupiah against the US Dollar). Research Methods: the research approach utilizes a Multi-output Deep Neural Network (DNN) with a Back-propagation algorithm to model the input-output relationship. The method can provide forecasting results for two or more bivariate or multivariate output variables. Finding/Results: The modeling analysis results indicate that the optimal model network structure is DNN (3.4). This model successfully predicts output 1 (export value) and output 2 (import value) with Mean Absolute Percentage Error (MAPE) rates of 13.76% and 13.63%, respectively. Additionally, the forecasting results show predicted export and import values for November to be US$ 16,208.13 billion and US$ 15,105.33 billion, respectively. These findings offer important insights into the direction of Indonesia's international trade movement, which can serve as a basis for future economic decision-making.
Co-Authors A. Tuti Rumiati Abdul Karim Abdul Karim Adatul Mukarohmah Affandy*, Nur Azizah Ahsan, Muhammad Akhmad Faturohman Bambang Widjanorko Otok Bambang Widjanorko Otok Budi Manfaat budi manfaat, budi Danny Hermawan Adiwibowo Data Iranata dwi purwanto Eksiandayani, Santi Era Ardhya Pramesti Erma Oktania Permatasari Faturohman, Akhmad Fithriasari, Kartika Forestryani, Veniola Fredi Suryadi Fredi Suryadi Hendri Prabowo Heri Kuswanto Hidayatul Khusna Husna Miratin Nuroini Ismaini Zain Luh Putu Shintya Handayani Maharsi, Rengganis Woro Maulana, Mahendra Andiek Muhammad Hisyam Lee Muhammad Sjahid Akbar Nadjadji Anwar Novi Ajeng Salehah Prandipa, Rayza Pusaka, Semerdanta Rhifda Zukhrufi Rizki Nanda Savera Roosyidah, Nila Ayu Nur S Suhartono, S Salafiyah Isnawati Santi Puteri Rahayu Saputra, Wisnowan Hendy Setiawan Setiawan Setiawan Setiawan Shofi Andari Suhartono Suhartono Suhartono Suhartono Suhartono Suhartono Supriyatna, Putu Krishnanda Veniola Forestryani Vita Ratnasari Wardoyo, Wasis Wibawati Wibawati Widhianingsih, Tintrim Dwi Ary Yusop, Zulkifli