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All Journal UNP Journal of Statistics and Data Science
Nisa, Farras Luthfyah
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Computer Science & IT Decision Sciences, Operations Research & Management Mathematics Social Sciences

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Peramalan Harga Beras di Kota Padang untuk Tahun 2025 Menggunakan Jaringan Syaraf Tiruan dengan Metode Backpropagation Nisa, Farras Luthfyah; Dony Permana; Denny Armelia
UNP Journal of Statistics and Data Science Vol. 3 No. 4 (2025): UNP Journal of Statistics and Data Science
Publisher : Departemen Statistika Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ujsds/vol3-iss4/381

Abstract

Rice is a staple food commodity in Indonesia that significantly influences economic stability and food security. In Padang City, rice price fluctuations frequently occur due to high dependence on external supply sources and limited local production, highlighting the need for a reliable predictive system. This study aims to forecast the monthly average retail price if rice in Padang City for the year 2025 using an Artificial Neural Network (ANN) based on the Backpropagation algorithm. The forecasting model is developed using historical rice price data from January 2017 to December 2024. In addition to building the forecasting model, this study evaluates the model’s accuracy in capturing the complex and nonlinear patterns of rice price fluctuations. The forecasting results are expected to serve as a valuable reference for local policymakers, market participants, and consumers in making strategic decisions to anticipate future price volality.
Co-Authors Denny Armelia Dony Permana