Research Article Open Access

FUZZY MODEL OPTIMIZATION FOR TIME SERIES DATA USING A TRANSLATION IN THE EXTENT OF MEAN ERROR

Nurhayadi 1, Subanar 2, Abdurakhman 2 and Agus Maman Abadi3
  • 1 Tadulako University, Indonesia
  • 2 Gadjah Mada University, Indonesia
  • 3 Yogyakarta State University, Indonesia

Abstract

Recently, many researchers in the field of writing about the prediction of stock price forecasting, electricity load demand and academic enrollment using fuzzy methods. However, in general, modeling does not consider the model position to actual data yet where it means that error is not been handled optimally. The error that is not managed well can reduce the accuracy of the forecasting. Therefore, the paper will discuss reducing error using model translation. The error that will be reduced is Mean Square Error (MSE). Here, the analysis is done mathematically and the empirical study is done by applying translation to fuzzy model for enrollment forecasting at the Alabama University. The results of this analysis show that the translation in the extent of mean error can reduce the MSE.

Journal of Mathematics and Statistics
Volume 10 No. 2, 2014, 267-274

DOI: https://doi.org/10.3844/jmssp.2014.267.274

Submitted On: 1 April 2014 Published On: 2 June 2014

How to Cite: Nurhayadi, Subanar, Abdurakhman, & Abadi, A. M. (2014). FUZZY MODEL OPTIMIZATION FOR TIME SERIES DATA USING A TRANSLATION IN THE EXTENT OF MEAN ERROR. Journal of Mathematics and Statistics, 10(2), 267-274. https://doi.org/10.3844/jmssp.2014.267.274

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Keywords

  • Fuzzy Model
  • Time Series
  • Model Translation
  • Forecasting