DOI: https://doi.org/10.14710/j.gauss.10.3.325-336

PERBANDINGAN METODE DOUBLE EXPONENTIAL SMOOTHING HOLT DAN FUZZY TIME SERIES CHEN UNTUK PERAMALAN HARGA PALADIUM

*Anes Desduana Selasakmida  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Tarno Tarno  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Triastuti Wuryandari  -  Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro, Indonesia
Open Access Copyright 2021 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

Palladium is one of the precious metal commodities with the best performance since 3 years ago. Palladium has many benefits, including being used in the electronics, medical, jewelry and chemical industries. The benefits of palladium in the chemical field are that it can help speed up chemical reactions, filter out toxic gases in exhaust gases, and convert the gas into safer substances, so palladium is usually used as a catalyst for cars. Forecasting is a process of processing past data and projected for future interest using several mathematical models. The model used in this study is the Double Exponential Smoothing Holt and Fuzzy Time Series Chen methods. The process of forecasting palladium prices using monthly data from January 2011 to December 2020 with the Double Exponential Smoothing Holt method and the Fuzzy Time Series Chen method will be carried out in this study to describe the performance of the two methods. Based on the results of the analysis, it can be concluded that the Double Exponential Smoothing Holt and Fuzzy Time Series Chen methods have equally good performance with sMAPE values of 6.21% for Double Exponential Smoothing Holt and 9.554% for Fuzzy Time Series Chen. Forecasting for the next 3 periods using these two methods generally produces forecasting values that are close to the actual data.

 

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Keywords: Palladium Price; Holt Double Exponential Smoothing; Chen Fuzzy Time Series; sMAPE

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  7. Kusumadewi, S., & Purnomo, H. (2004). Aplikasi Logika Fuzzy Untuk Pendukung Keputusan. Yogyakarta: Penerbit Graha Ilmu
  8. Kusumadewi, S., & Purnomo, H. (2010). Aplikasi Logika Fuzzy untuk Pendukung Keputusan Edisi 2. Jogjakarta: Graha Ilmu
  9. Larasati, L. (2018). Makalah Paladium. 13
  10. Li-xin, W. (1997). A Course in Fuzzy Systems And Control International edition
  11. Makridakis, S. ,. (2000). The M3-Competition: Result, Conclusion and Implications. Internasional Journal of Forcasting , Vol.16, Hal:451-476
  12. Makridakis, S., & Wheelwright, S. C. (1983). Forecasting:Method and Aplication. Canada: John Wiley dan Sons
  13. Makridakis, S., Wheelwright, S. C., & McGee, V. E. (1999). Metode dan Aplikasi Peramalan. Jakarta: Binarupa Aksara
  14. Mansyur, & Rohadi, E. (2015). Sistem Informasi Peramalan Stok Barang di CV. Annora Asia Menggunakan Metode Double Exponential Smoothing. Jurnal Informatika Polinoma , 45-49
  15. Rahayu, Sri. (2005). SPSS Versi 12.00 dalam Riset Pemasaran. Bandung:Alfabeta
  16. Somantri, A., & Muhidin, S. A. (2006). Aplikasi Statistika Dalam Penelitian. Bandung: Pustaka Ceria.Steven, S., Nurdiati, S., & Bukhari, F. (2018). Perbandingan Metode Fuzzy Time Series dan Holt Double Exponential Smoothing Pada Peramalan Jumlah Mahasiswa Baru Institut Pertanian Bogor. Jurnal Matematika dan Aplikasinya , 12(2)
  17. Syafputri, E. (2012). Investasi Emas Dinar dan Dirham. Jakarta: Penebar Plus
  18. Utama, C. A., & S, Y. W. (2016). Pengembangan SI Stok Barang Dengan Permalan Menggunakan Metode Double Exponential Smoothing (Studi Kasus:PT. Tomah Jaya Elektrikal). Jurnal Informatika Polinema , 147-153
  19. Yapar, G., Capar, S., Taylan, H., & Yavuz, I. (2018). Modified Holt's Linear Trend Method. Hacettepe Journal of Mathematics and Statistics , Vol. 47(5) Page. 1394-1403
  20. Zadeh, A. L. (1965). Fuzzy Sets. Jurnal Information and Control , Vol.8:338-353

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