PERAMALAN DATA PRODUK DOMESTIK BRUTO DENGAN FUZZY TIME SERIES MARKOV CHAIN

Authors

  • Maria Titah Jatipaningrum Jurusan Statistika, Fakultas Sains Terapan Institut Sains & Teknologi AKPRIND Yogyakarta

Keywords:

Fuzzy time series Markov chain, Produk Domestik Bruto, grup logika fuzzy

Abstract

Penelitian ini membahas pendekatan fuzzy time series Markov chain untuk menganalisis data linguistik atau data time series sampel kecil diusulkan supaya keakuratan prediksi lebih tinggi dengan mentransfer data time series ke grup logika fuzzy, dan menggunakannya untuk mendapatkan matriks transisi Markov chain kemudian digunakan untuk peramalan. Makalah ini berusaha untuk meningkatkan akurasi peramalan dengan Markov chain dan klasifikasi dari ruang keadaan. Metode ini diterapkan pada data time series Produk Domestik Bruto. Pengujian dilakukan untuk melihat akurasi peramalan dengan MAPE (Mean Average Percentage Error).

Kata Kunci— , Produk Domestik Bruto,

Downloads

Download data is not yet available.

References

Berutu, S.S 2013. Peramalan Penjualan dengan Metode Fuzzy Time Series Ruey Chyn Tsaur, Thesis, Program Studi Magister Sistem Informasi, Universitas Diponegoro, Semarang.
Chen, S. 1996. Forecasting Enrollment Based on Fuzzy Time Series. Fuzzy sets and systems, 81(3): 311-319.
Cheng, C. H., Cheng, G. W., dan Wang, J. W. 2008. Multi-attribute Fuzzy Time Series Method Based on Fuzzy Clustering. Expert systems with applications, 34(2), pp.1235-1242.
Li, S.T. dan Cheng, Y. C. 2007. Deterministic Fuzzy Time Series Model For Forecasting Enrollment. Computers and mathematics with application, 53(12): 1904-1920.
Melike, S. dan Degtiarev, K. Y. 2005. Forecasting Enrollment Model Based on First Order Fuzzy Time Series. Proceedings of world academy of science, engineering and technology, 1: 132-135.
Rosadi, D., 2006, Pengantar Analisa Runtun Waktu, http://dedirosadi.staff.ugm.ac.id, diakses tanggal 18 November 2015.
Singh, S. R. 2007. A Simple Method of
Forecasting Based on Fuzzy Time Se ries. Applied mathematic and computation, 186(1): 330-339.
Song, Q. dan Chissom, B. S. 1993. Forecasting Enrollment With Fuzzy Time Series- Part I. Fuzzy sets and systems, 54(1): 1-9.
Stevenson, M. dan Porter, J. E. 2009. Fuzzy Time Series Forecasting Using Percentage Change As the Universe of Discourse. World academy of science, engineering and technology, 55: 154-157.
Sullivan, J. and W.H. Woodall, (1994), A comparison of fuzzy forecasting and Markov modeling, Fuzzy Sets and Systems. 64 279–293
Tsaur, R. C. 2012. A Fuzzy Time Series- Markov Chain Model With an Application to Forecast the Exchange Rate Between the Taiwan and US Dollar. International journal of innovative computing,information and control, 8(7B): 4931-4942.
Tsaur, R. C., Yang, J.C.0., dan Wang, H. F. 2005. Fuzzy relation Analysis in Fuzzy Time Series Model. Computer and mathematics with applications, 49(4):
539-548.
Yu, H. 2005.Weighted Fuzzy Time Series Models For Taiex Forecasting. Physica A, 349: 609-624.

Downloads

Published

2016-06-30

How to Cite

Jatipaningrum, M. T. (2016). PERAMALAN DATA PRODUK DOMESTIK BRUTO DENGAN FUZZY TIME SERIES MARKOV CHAIN. Jurnal Teknologi, 9(1), 31–38. Retrieved from https://ejournal.akprind.ac.id/index.php/jurtek/article/view/1137