Fuzzy Time Series Orde Tinggi berdasarkan Rasio Interval
DOI:
https://doi.org/10.25077/jmu.11.1.53-63.2022Abstract
Fuzzy time series (FTS) adalah metode peramalan untuk memprediksi data time series dibentuk dalam nilai-nilai linguistik yang diperkenalkan pertama kali oleh Song dan Chissom. Metode peramalan FTS terus berkembang misalnya pengembangan pada partisi interval pembicaraan menggunakan rasio interval oleh Huarng dan pengembangan pada fuzzy logical relationship (FLR) orde tinggi oleh Chen. Penelitian ini memodifikasi metode Chen pada langkah partisi interval pembicaraan menggunakan rasio interval untuk meningkatkan akurasi peramalan. Langkah pertama adalah pembentukan semesta pembicaraan. Kedua, mempartisi semesta pembicaraan menjadi beberapa interval dengan menggunakan rasio interval. Ketiga, fuzzyfikasi. Keempat, membangun relasi logika fuzzy (FLR) dan grup relasi logika fuzzy (FLRG). Kelima, defuzzyfikasi. Hasil penggabungan metode Huarng-Chen dibandingkan dengan metode Chen. Simulasi yang dilakukan menggunakan data produksi karet Indonesia tahun 2000-2020. Hasil dan eror dari metode diuji menggunakan mean square error (MSE) dan average forecasting error rate (AFER). Diperoleh hasil modifikasi menghasilkan eror yang lebih kecil daripada metode sebelumnya.
References
Chen, S.M., 1996, emph{Forecasting enrollments based on fuzzy time series}, emph{Fuzzy Sets Syst.},textbf{volume 81} : halaman 311-319.
Chen, S.M., 2002, emph{Forecasting enrollments based on high-order fuzzy time series}, emph{Cybern. Syst.},textbf{volume 33, nomor 1} : halaman 1-16.
Huarng, K.,Yu, T.H.K., 2006, emph{Ratio-based lengths of intervals to improve fuzzy time series forecasting}, emph{IEEE Trans. Syst. Man, Cybern. Part B Cybern},textbf{volume 36, nomor 2} : halaman 328-340.
Mashuri, C., Suryono, S., Suseno, J.E. , 2018, emph{Prediction of Safety Stock Using Fuzzy Time Series (FTS) and Technology of Radio Frequency Identification (RFID) for Stock Control at Vendor Managed Inventory (VMI)}, emph{E3S Web Conf.},textbf{volume 31} : halaman 0-4.
Suesut, T., Gulphanich, S., Nilas, P., Roengruen, P., Tirasesth, K. , 2004, emph{Demand forecasting approach inventory control for warehouse automation}, emph{IEEE Reg. 10 Annu. Int. Conf. Proceedings/TENCON},textbf{volume B} : halaman 438-441.
News, A. 10 negara penghasil karet alami terbesar di dunia, 2021, diakses 21 Desember 2021.
Suryana, A., Goenadi, D.H., Supriadi, M., Wibawa, G., Sarjono, M., Hadi, P.U., 2007, emph{Prospek dan Arah Pengembangan Agribisnis Karet}, Edisi ke-2, Badan Litbang Pertanian, Jakarta.
Lee, L.W., Wang, L.H., Chen, S.M., Leu, Y.H., 2006, emph{Handling forecasting problems based on two-factors high-order fuzzy time series}, emph{IEEE Trans. Fuzzy Syst.},textbf{volume 14, nomor 3} : halaman 468-477.
Downloads
Additional Files
Published
Issue
Section
License
All articles published in Jurnal Matematika UNAND (JMUA) are open access and licensed under the Creative Commons Attribution-ShareAlike (CC BY-SA) license. This ensures that the content is freely available to all users and can be shared and adapted, provided appropriate credit is given and any adaptations are distributed under the same license.
Copyright Holder
The copyright of all articles published in Jurnal Matematika UNAND is held by the Departemen Matematika dan Sains Data, Fakultas Matematika dan Ilmu Pengetahuan Alam (FMIPA), Universitas Andalas (UNAND). This applies to all published versions, including the HTML and PDF formats of the articles.
Author Rights
While the Departemen Matematika dan Sains Data FMIPA UNAND holds the copyright for all published content, authors retain important rights under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA). This license grants authors and users the following rights:
- Reuse: Authors can reuse and distribute their work for any lawful purpose, including sharing on personal websites, institutional repositories, or in subsequent publications.
- Attribution and Adaptation: Authors and others may remix, adapt, and build upon the published work for any purpose, even commercially, as long as proper credit is given to the original authors, and any derivative works are distributed under the same CC BY-SA license.
Creative Commons License (CC BY-SA)
Under the terms of the CC BY-SA license, users are free to:
- Share: Copy and redistribute the material in any medium or format.
- Adapt: Remix, transform, and build upon the material for any purpose, even commercially.
However, the following conditions apply:
- Attribution: Users must give appropriate credit to the original author(s) and Departemen Matematika dan Sains Data FMIPA UNAND, provide a link to the license, and indicate if changes were made. Attribution must not imply endorsement by the author or the journal.
- ShareAlike: If users remix, transform, or build upon the material, they must distribute their contributions under the same license as the original.
For more information about the CC BY-SA license, please visit the Creative Commons website.
Third-Party Content
If authors include third-party material (such as figures, tables, or images) that is not covered by a Creative Commons license, they must obtain the necessary permissions for reuse and provide proper attribution. Authors are required to ensure that any third-party content complies with open-access licensing requirements or includes permissions for redistribution under similar terms.
Copyright and Licensing Information Display
The copyright and licensing terms will be clearly displayed on each article's landing page, as well as within the full-text versions (HTML and PDF) of all published articles.
No "All Rights Reserved"
As an open-access journal, JMUA does not use "All Rights Reserved" policies. Instead, the CC BY-SA license ensures that the works remain accessible and reusable for a wide audience while still protecting both the authors' and the copyright holder's rights.
Â









