Forecasting Motorcycle Sales Using Nearest Symmetric Trapezoidal Fuzzy Number
Abstract
A business activity aimed at obtaining forecasting as an initial step in planning activities helps provide an overview of sales in a business for the coming period based on data available. This research aims to design and develop a motorcycle sales forecasting application using Fuzzy Time Series with Nearest Symmetric Trapezoidal Fuzzy Number approach to predict the next period sales of PT Mutiara Motor. To test the accuracy of the method used in application, we used the MSE and MAPE criteria. Based on the results of three experiments taken: (1) monthly ‘All Category’-’All Type’ with MSE = 54.42 and MAPE = 4.28%, (2) monthly ‘Beat CW Fuel Injection’ with MSE = 3.67 and MAPE = 4.04%, and (3) daily ‘All Category’- ’All Type’ with MSE = 1.42 and MAPE = 27.36% we indicate that Fuzzy Time Series with Nearest Symmetric Trapezoidal Fuzzy Number approach could give higher accuracy than the Single Exponential Smoothing method as comparison in forecasting motorcycle sales.
Index Terms—fuzzy time series, nearest symmetric trapezoidal fuzzy number, sales forecasting
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