Vegetable Price Forecasting Model in an Agricultural Knowledge Management System Using Genetic Algorithm-Based Neural Network

Abstract

Knowledge management system (KMS) is a technology that helps teams gather, organize, and share information across a business and for its customers. However, the lack of KMS in Malaysia and low national interest in agriculture worsen the problem in Malaysia's agriculture sector. Food production and productivity are declining in Malaysia while food consumption is rising. Other issues include a bias toward oil palm plantations, unfair prices for farmers' crops, aging and unskilled farmers and fishermen, reliance on imported food, supply channel bottlenecks, and a lack of market understanding.  In recent years, Malaysia's government is started to put effort into agricultural development. Therefore, the authors aim to design and develop a platform with multi-purpose such as E-Commerce and information sharing using KMS. However, this paper focuses on implementing the vegetable price forecasting model, which utilises the Genetic Algorithm based Neural Network. In the end of this paper, it shows the forecasted vegetable price data with high accuracy compared to the traditional models.