Fuzzy Logic using Tsukamoto Model and Sugeno Model on Prediction Cost

Abstract

Abstract-This paper aims to implement Fuzzy Logic for cost prediction. Fuzzy Logic using Tsukamoto Model and Sugeno Model. Predicted costs consist of communication cost, transportation cost, and social cost as the external cost. The external cost is one component of living cost. High external cost becomes one of the causes of the high cost of living. The high cost of living is one of the factors causing high-cost economy. In this case, the cost prediction using Fuzzy Logic. Experimental results show that Fuzzy Logic using Tsukamoto Model with value is 1891. Fuzzy Logic using Sugeno Model with value 1621. Both models produce a feasible cost prediction. Feasible is meaning accurate and proper (value cost between low cost and high cost from all of cost). There are 46.56 % of the population of middle class in Indonesia. This means that 46.56% of the population of Indonesia has the potential to reduce the high cost economy. High cost economy (living cost) can be reduced, it can drive economic growth (social cost) and be able to improve social welfare (social cost).

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“…T and U in formula (5) and 6are adjusted with a fuzzy logic function combining fuzzy rules and a subordinating degree function. This paper adopts a Sugeno fuzzy logic model [17] (i.e., TS) that are effective in nonlinearity to adjust the Kalman filter's parameters. This paper defines the following fuzzy logic rules R i : :…”

“…We calculate monitored residual errors' variance with formula (17) and predict residual errors' variance with formula (13), and then compare them. When the monitored mean is much bigger than zero, and the monitored variance is much bigger than the predicted variance, we adjust the noise matrix to improve the Kalman filter's precision.…”