KOMPARASI KINERJA FUZZY TIME SERIES DENGAN MODEL RANTAI MARKOV DALAM MERAMALKAN PRODUK DOMESTIK REGIONAL BRUTO BALI

  • I MADE ARYA ANTARA Faculty of Mathematics and Natural Sciences, Udayana University
  • I PUTU EKA N. KENCANA Faculty of Mathematics and Natural Sciences, Udayana University
  • I KOMANG GDE SUKARSA Faculty of Mathematics and Natural Sciences, Udayana University

Abstract

This paper aimed to elaborates and compares the performance of Fuzzy Time Series (FTS) model with Markov Chain (MC) model in forecasting the Gross Regional Domestic Product (GDRP) of Bali Province.  Both methods were considered as forecasting methods in soft modeling domain.  The data used was quarterly data of Bali’s GDRP for year 1992 through 2013 from Indonesian Bureau of Statistic at Denpasar Office.  Inspite of using the original data, rate of change from two consecutive quarters was used to model. From the in-sample forecasting conducted, we got the Average Forecas­ting Error Rate (AFER) for FTS dan MC models as much as 0,78 percent and 2,74 percent, respec­tively.  Based-on these findings, FTS outperformed MC in in-sample forecasting for GDRP of Bali’s data.

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Author Biographies

I MADE ARYA ANTARA, Faculty of Mathematics and Natural Sciences, Udayana University
Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
I PUTU EKA N. KENCANA, Faculty of Mathematics and Natural Sciences, Udayana University
Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
I KOMANG GDE SUKARSA, Faculty of Mathematics and Natural Sciences, Udayana University
Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University
Published
2014-08-29
How to Cite
ANTARA, I MADE ARYA; N. KENCANA, I PUTU EKA; SUKARSA, I KOMANG GDE. KOMPARASI KINERJA FUZZY TIME SERIES DENGAN MODEL RANTAI MARKOV DALAM MERAMALKAN PRODUK DOMESTIK REGIONAL BRUTO BALI. E-Jurnal Matematika, [S.l.], v. 3, n. 3, p. 116 - 122, aug. 2014. ISSN 2303-1751. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/12002>. Date accessed: 21 nov. 2024. doi: https://doi.org/10.24843/MTK.2014.v03.i03.p073.
Section
Articles

Keywords

domestic product; fuzzy modeling; in-sample forecasting; Markov chain

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