Prediksi Nilai Ekspor Indonesia Menggunakan Metode Artificial Neural Network (ANN)
DOI:
https://doi.org/10.62712/juktisi.v4i3.807Keywords:
Artificial Neural Network, Prediksi Nilai Ekspor, Ekspor Indonesia, Data Deret Waktu, Peramalan EkonomiAbstract
Exports are one of the main indicators of Indonesia's economic growth. To assist in planning and policymaking, accurate prediction techniques are needed because various factors influence export value fluctuations. Using the Artificial Neural Network (ANN) method, this study aims to predict Indonesia's export value. The data used comes from official sources and is processed through preprocessing, normalization, and the division of training and test data. To predict export value, an ANN model is built and trained to recognize patterns of relationships between data. The results show that the ANN method can predict Indonesia's export value with a high degree of accuracy. Therefore, the ANN method can be used as an effective alternative for predicting export value and assisting economic decision-making
Downloads
References
A. M. Ginting, “Analisis pengaruh ekspor terhadap pertumbuhan ekonomi Indonesia (An analysis of export effect on the economic growth of Indonesia),” Buletin Ilmiah Litbang Perdagangan, vol. 11, no. 1, pp. 1–20, 2017.
A. dkk., “Pengaruh ekspor terhadap pertumbuhan ekonomi Indonesia (Effect of export on Indonesian’s economic growth),” Jurnal Ekonomi dan Kebijakan Pembangunan, vol. 5, no. 2, pp. 10–31, 2016.
A. Farida and I. Yuliana, “Pengaruh utang luar negeri dan ekspor terhadap pertumbuhan ekonomi (PDB) Indonesia periode 2006–2020,” MALIA, vol. 13, no. 2, pp. 181–192, Jul. 2022, doi: 10.35891/ml.v13i2.3016.
O. I. Abiodun, A. Jantan, A. E. Omolara, K. V. Dada, N. A. Mohamed, and H. Arshad, “State-of-the-art in artificial neural network applications: A survey,” Heliyon, vol. 4, p. e00938, 2018, doi: 10.1016/j.heliyon.2018.e00938.
H. Kukreja, “Introduction to artificial neural networks,” IJARIIE, vol. 1, no. 5, pp. 27–30, 2016.
O. I. Abiodun et al., “Comprehensive review of artificial neural network applications to pattern recognition,” IEEE Access, vol. 7, pp. 158820–158846, 2019, doi: 10.1109/ACCESS.2019.2945545.
M. D. A. Nasution, J. T. Hardinata, and I. S. Damanik, “Jaringan syaraf tiruan backpropagation untuk klasifikasi data tilang berdasarkan jenis pelanggaran,” in Prosiding Seminar Nasional Riset Information Science (SENARIS), 2019, pp. 547–556.
U. Janssens, “Functional hemodynamic monitoring,” 2024, doi: 10.1007/s00063-024-01190-4.
T. Yuniarti, I. Rusmar, T. R. Hidayani, M. Mirnandaulia, and P. Teknologi Kimia Industri, “Penggunaan artificial neural network (ANN) untuk memodelkan volume ekspor crude palm oil (CPO) di Indonesia,” Ready Star, vol. 2, no. 1, pp. 247–255, 2019.
M. Thoriq, “Peramalan jumlah permintaan produksi menggunakan jaringan saraf tiruan algoritma backpropagation,” Jurnal Informasi dan Teknologi, vol. 4, no. 1, pp. 27–32, 2022, doi: 10.37034/jidt.v4i1.178.
M. I. Syahroni, “Prosedur penelitian kualitatif,” Jurnal Al-Musthafa STIT Al-Aziziyah Lombok Barat, vol. 2, no. 3, pp. 43–56, 2022.
N. M. Haifa, I. Nabilla, V. Rahmatika, and R. Hidayatullah, “Identifikasi variabel penelitian dan jenis sumber data dalam penelitian pendidikan,” Jurnal Pendidikan dan Bahasa, vol. 2, no. 2, pp. 256–270, 2025.
N. Sinulingga, M. I. Sarif, N. A. Ramadhani, and K. Nurfebia, “Penerapan algoritma K-Means clustering untuk mengetahui pola peminjaman buku di Perpustakaan Universitas Imelda Medan,” vol. 4, no. 3, pp. 1558–1566, 2026.
W. Musu, A. Ibrahim, and H. Heriadi, “Pengaruh komposisi data training dan testing terhadap akurasi algoritma C4.5,” SISITI: Seminar Ilmiah Sistem Informasi dan Teknologi Informasi, vol. 10, no. 1, pp. 186–195, 2021, doi: 10.36774/sisiti.v10i1.802.
N. A. Purwitasari and M. Soleh, “Implementasi algoritma artificial neural network dalam pembuatan chatbot menggunakan pendekatan natural language processing,” Jurnal IPTEK, vol. 6, no. 1, pp. 14–21, 2022, doi: 10.31543/jii.v6i1.192.
E. Saraswati, Y. Umaidah, and A. Voutama, “Penerapan algoritma artificial neural network untuk klasifikasi opini publik terhadap COVID-19,” Generation Journal, vol. 5, no. 2, 2021.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Rahul Sinurat, Arion Tampubolon, Irene Lestaria sinaga, Monica Sari Batubara, Novita sari siagian, jaya tatahardinata

This work is licensed under a Creative Commons Attribution 4.0 International License.















