Price Prediction System of Basic Commodities Using Long Short-Term Memory Method: Analysis and Implementation for Future Projections

Rifqi Fahrudin, Kusnadi Kusnadi, Chandra Lukita
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Abstract

The uncontrollable prices of basic commodities, especially food commodities, have resulted in losses for producers and consumers in the city of Cirebon. To be able to bridge these problems, it is necessary to make the right decisions. A prediction system is one of the elements that can be used to support the right decision-making. Predictions in decision-making are based on existing data at present and in the past so that they can be used to describe conditions in accordance with the objectives achieved. With an accurate price prediction system for staple food commodities, it is hoped that decision-making will be able to decide on good policies from the Cooperative, Small and Medium Enterprises Service for Trade and Industry (DKUKMPP) for the people of Cirebon City. The method used is Long Short-Term Memory (LSTM). The data used for the basic prices of food commodities, namely the last 3 years in 2020 - 2022, are sourced from the official website of the Ministry of Trade's Market Monitoring System and Basic Needs using Google Colab tools. 
使用长短期记忆法的基本商品价格预测系统:未来预测的分析与实施
无法控制的基本商品价格,尤其是食品价格,给井里汶市的生产者和消费者造成了损失。为了解决这些问题,必须做出正确的决策。预测系统是支持正确决策的要素之一。决策中的预测是以当前和过去的现有数据为基础的,这样就可以根据所实现的目标来描述条件。有了准确的主食商品价格预测系统,我们希望决策层能够为井里汶市的人民决定来自贸工部中小型企业服务局(DKUKMPP)的好政策。使用的方法是长短期记忆法(LSTM)。使用谷歌 Colab 工具从贸易部的市场监测系统和基本需求的官方网站获取食品商品基本价格的数据,即 2020 - 2022 年的最近 3 年的数据。
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