Analysis and Design of a Food Price Prediction System using the Iconix Process Method

Abstract

The need for food is very important for human survival. Therefore, food prices have a very big influence. Several factors cause unstable food prices, including increased demand during major holidays, and seasonal or weather factors that result in crop failure. Because of these factors, price increases can occur at any time and have an impact on society if prices rise unexpectedly. Based on these problems, a system was designed to predict food prices using the Iconix system development method, and to calculate price predictions using the Least Square method. In this system, analysis and system design is carried out to predict food prices. The predicted food ingredients will be limited to ten food ingredients, namely rice, shallots, garlic, red chilies, cayenne peppers, beef, chicken, granulated sugar, cooking oil and purebred chicken eggs. The process design used to describe information systems is the design of system flow diagrams, use case diagrams, sequence diagrams, activity diagrams. Black Box testing provides results that each feature in the food price prediction system has been successfully created and functions well.