Arima model and fuzzy mamdani in the Kijang Emas transactions

Abstract

This paper represents a design procedure for Mamdani Fuzzy logic controller including rule base minimization. The rules are modeled with binary weights on which constraints are imposed in order to ensure consistency. At the beginning steps, time series ARIMA is used to forecast the buying and selling price of Kijang Emas which weight 1 oz The ARIMA model has four main stages which are model identification, parameter estimation, diagnostic checking and forecasting. After that, the buying and selling price of gold bullion coins are used by Fuzzy Mamdani method for finding stabilizing controllers that minimize the number of rules. The number of fuzzy sets for the input and the control variables are set by the user and the design procedure is concerned only with the rule base and the distribution of the fuzzy sets in the universes of discourses.