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All Journal JIKSI (Jurnal Ilmu Komputer dan Sistem Informasi) Jurnal Esensi Infokom: Jurnal Esensi Sistem Informasi dan Sistem Komputer
Matthew Oni
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Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Mathematics Other

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PREDIKSI HARGA PANGAN KOTA BANDUNG MENGGUNAKAN METODE GATED RECURRENT UNIT Matthew Oni; Manatap Dolok Lauro; Teny Handhayani
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 11 No. 2 (2023): JURNAL ILMU KOMPUTER DAN SISTEM INFORMASI
Publisher : Fakultas Teknologi Informasi Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/jiksi.v11i2.26014

Abstract

Food problems often occur among the community, this occurs due to a lack of predictions made to determine future food prices. Food prices can be achieved if the government can provide sufficient food supplies both in terms of quality and quantity. The availability of sufficient food is an important factor in maintaining the health and welfare of the community. However, the high price fluctuations of staple foods in traditional markets have a negative impact on the availability and quality of food for the community, especially those with low incomes. This was caused by various factors such as rising raw material prices, the influence of weather factors, and changes in people's consumption patterns. In addition, the process of distribution and marketing of staple foods in traditional markets in Bandung City, which still relies on manual processes and is less structured, can also cause high price fluctuations. Therefore we need an application to predict staple food needs for the future accurately and effectively. This study uses the Gated Recurrent Unit method. This method is used because the Gated Recurrent Unit method has good performance in making predictions and fits the data used for this study. In this study, there were 5 types of commodities used, namely rice, chicken meat, chicken eggs, shallots, and garlic. All datasets used were taken from the website of the National Strategic Food Price Information (PIHPSNasional, https://www.bi.go.id/hargapangan). Predictive results by evaluating MAE and MAPE for rice 12.8, and 0.10, for chicken meat 12.8 , and 0.10, for chicken egg 244.5, and 0.64, for onion 296.9, and 1.05, for garlic 602.8, and 1.32.
Analysis And Forecasting of Foodstuffs Prices in Bandung Using Gated Recurrent Unit Matthew Oni; Manatap Dolok Lauro; Andry Winata; Teny Handhayani
Jurnal Esensi Infokom : Jurnal Esensi Sistem Informasi dan Sistem Komputer Vol 7 No 2 (2023): Jurnal Esensi Infokom : Jurnal esensi sistem informasi dan sistem komputer
Publisher : Lembaga Riset dan Pengabdian Masyarakat Institut Bisnis Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55886/infokom.v7i2.651

Abstract

Bandung is a city in West Java province, Indonesia. Bandung becomes one of the most densely populated cities in Indonesia. Therefore, predicting and analyzing the prices of foodstuffs based on historical data is necessary to provide useful information for society and government. This paper developed models implementing a gated recurrent unit or GRU which is a specific version of recurrent neural networks (RNN) for forecasting the price of rice, chicken meat, chicken egg, shallot, and garlic in a Bandung traditional market. The GRU models are trained using a dataset from the Information Center for National Strategic Food Price. The data are recorded from January 2018 – February 2023. The experimental results show that GRU was successfully implemented for forecasting the price of rice, chicken meat, chicken egg, shallot, and garlic. The best models produce Mean Absolute Error (MAE) as 4.3, 133.1, 118.3, 341.8, and 338.1 for rice, chicken meat, chicken egg, shallot, and garlic, respectively.
Co-Authors Andry Winata Laksono Trisnantoro Manatap Dolok Lauro, Manatap Dolok Teny Handhayani