Artificial Intelligence In Cooking Oil Price Prediction Using the Fuzzy Inference System Concept

Abstract

At the end of 2021 in October the price of cooking oil increased very sharply in packaged cooking oil and bulk cooking oil. Cooking oil had recorded a deflation in February 2022 of 0.11%, then increased again with a deflation of 0.04%. The causes of the increase in oil consist of 4 types including very sharp international oil prices, reduced oil production caused by disruptions in the distribution chain, increase in demand and the last one. Logistical disruptions during the Covid-19 pandemic, such as the reduced number of containers in the cooking oil delivery process. The problem that will be discussed in this study is to see the cause of the increase in cooking oil in the market. The purpose of this study is to examine the causes of the increase in cooking oil prices and the development of market prices for cooking oil circulating in the market. The basic concept of this research uses the concept of Marketing Management and Artificial Intelligence using Sugeno's Fuzzy Logic Method. The criterion variable consists of 4 input variables 1. Oil Price, 2 Cooking Oil Production, 3 Demand and the fourth is Logistics Disorder while the output variable produces a Normal Decision with a value of 0, Expensive with a value of 1. The final result of this study obtains an Output value of 0, 85 which is in the Expensive range. To find out the other x values, it is enough to enter the x value into each search to find out the next output value which can be used as a reference in predicting the current cooking oil price.