KOMPARASI METODE ANFIS DAN FUZZY TIME SERIES KASUS PERAMALAN JUMLAH WISATAWAN AUSTRALIA KE BALI

  • IDA BAGUS KADE PUJA ARIMBAWA K. Faculty of Mathematics and Natural Sciences, Udayana University
  • KETUT JAYANEGARA Faculty of Mathematics and Natural Sciences, Udayana University
  • I PUTU EKA NILA KENCANA Faculty of Mathematics and Natural Sciences, Udayana University

Abstract

This study compares the accuracy of forecasting using ANFIS and Fuzzy Time Series the number of Australian tourists to Bali. The data used in this study are data on the number of Australia tourists visit to Bali from the period January 2006 through December 2011. ANFIS consists of two stages of learning and testing phases. Least Squares Estimator is used to study the forward direction and Error Back Propagation learning is used in the reverse direction. Forecasting with Fuzzy Time Series is forecast to capture the pattern of previous data is then used to project the data to come. The results of comparison of both methods showed that the ANFIS method has a higher forecasting accuracy than the method of Fuzzy Time Series. Forecasting by using ANFIS method obtained AFER aqual to 9,26% while the prediction using the method of Fuzzy Time Series obtained AFER aqual to 14,02%

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Author Biographies

IDA BAGUS KADE PUJA ARIMBAWA K., Faculty of Mathematics and Natural Sciences, Udayana University
Jurusan Matematika, FMIPA Universitas Udayana
KETUT JAYANEGARA, Faculty of Mathematics and Natural Sciences, Udayana University
Jurusan Matematika, FMIPA Universitas Udayana
I PUTU EKA NILA KENCANA, Faculty of Mathematics and Natural Sciences, Udayana University
Jurusan Matematika, FMIPA Universitas Udayana
Published
2013-05-31
How to Cite
PUJA ARIMBAWA K., IDA BAGUS KADE; JAYANEGARA, KETUT; KENCANA, I PUTU EKA NILA. KOMPARASI METODE ANFIS DAN FUZZY TIME SERIES KASUS PERAMALAN JUMLAH WISATAWAN AUSTRALIA KE BALI. E-Jurnal Matematika, [S.l.], v. 2, n. 2, p. 18-26, may 2013. ISSN 2303-1751. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/6287>. Date accessed: 22 nov. 2024. doi: https://doi.org/10.24843/MTK.2013.v02.i02.p033.
Section
Articles

Keywords

ANFIS; Fuzzy Time Series; Forecasting; Australian Tourist Forecasting