EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 483 (2024) E3S Web Conf., 483 (2024) 03001 References
Open Access
Issue
E3S Web Conf.
Volume 483, 2024
The 3rd International Seminar of Science and Technology (ISST 2023)
Article Number 03001
Number of page(s) 16
Section Trends in Mathematics and Computer Science for Sustainable Living
DOI https://doi.org/10.1051/e3sconf/202448303001
Published online 31 January 2024
  1. Chen & C. C. Hsu, “A new method to forecast enrollments using fuzzy time series”, Int. J. Appl. Sci. Eng., Vol 2, No. 3, 234–244 (2004). https://doi.org/10.6703/IJASE.2004.2(3).234 [Google Scholar]
  2. F. Fauzi, D. Agustuna, I. M. Nur, “Evaluasi Metode Fuzzy Time Series Cheng dan Ruey Chyn Tsaur [Evaluation Of Cheng and Ruey Chyn Tsaur’s Fuzzy Time Series Method]”, Jurnal Variance, Vol. 2, No. 2, (2021). https://doi.org/10.30598/variancevol3iss2page61-71 [Google Scholar]
  3. R.A. Fauzannissa, H. Yasin, D. Ispriyanti, “Peramalan Harga Minyak Mentah Dunia Menggunakan Metode Radial Basis Function Neural Network [Forecasting World Crude Oil Prices Using The Radial Basis Function Neural Network Method]”, Jurnal Gaussian, Vol 5, No 1 (2015) page 193–202, (2015). https://doi.org/10.14710/j.gauss.5.1.193-202 [Google Scholar]
  4. R. V. Febryo, G. Abdillah, R. Yuniarti, “Sistem Prediksi Harga Minyak mentah Dunia menggunakan Jaringan Syaraf tiruan dengan Backpropagation [World Crude Oil Price Prediction System using Artificial Neural Networks with Backpropagation]”, Prosiding SNIJA, (2015), ISBN 978-602-70361-1-6, Available at http://repository.unjani.ac.id/repository/c0c26ec68eba178dc02555b66e29bdde.pdf [Google Scholar]
  5. S. Herawati, M. Latif, “Peramalan Harga Minyak Mentah Menggunakan Ensemble Empirical Mode Decomposition dan Resilient Backpropagation [Forecasting Crude Oil Prices using Ensemble Empirical Mode Decomposition and Resilient Backpropagation]”, Seminar Teknologi dan Rekayasa (SENTRA), (2015). [Google Scholar]
  6. M. Hussein, Y. Azhar, “Prediksi Harga Minyak Dunia Dengan Metode Deep Learning [Predicting World Oil Prices Using the Deep Learning Method]”, Fountain Inform. J., Vol. 6, No. 1, (May, 2021), ISSN: 2541-4313 (Print)/ 2548-5113 (Online). https://doi.org/10.21111/fij.v6i1.4446 [Google Scholar]
  7. M. Muhammad, S. Wahyuningsih, M. Siringoringo, “Peramalan Nilai Tukar Petani Subsektor Peternakan Menggunakan Fuzzy Time Series Lee [Forecasting Exchange Rates for Farmers in the Livestock Subsector Using Lee Fuzzy Time Series]”, Jambura J. Math, Vol. 3, No. 1, pp. 1–15, (January 2021). https://doi.org/10.34312/jjom.v3i1.5940 [CrossRef] [Google Scholar]
  8. D. K. Natanael, D. Safitri, Suparti, “Prediksi Harga Minyak Dunia dengan Metode Autoregressive Fractionally Integrated Moving Average [Prediction of World Oil Prices using the Autoregressive Fractionally Integrated Moving Average Method]”, Jurnal Statistika Universitas Muhammadiyah Semarang, Vol 6, No 1 (2018). https://doi.org/10.26714/jsunimus.6.1.2018.%25p. Available at https://jurnal.unimus.ac.id/index.php/statistik/article/view/3425 [Google Scholar]
  9. M.A. Nizar, “Dampak Fluktiasi harga Minyak Dunia terhadap Perekonomian Indonesia [The Impact of World Oil Price Fluctuations on the Indonesian Economy]”, Buletin Ilmiah Litbang Perdagangan Vol 6, No 2 (2012). Available at https://jurnal.kemendag.go.id/bilp/article/view/131 [Google Scholar]
  10. A. Setiyono, A. Nurrahman. “Prediksi Harga Minyak Mentah Menggunakan Prophet [Crude Oil Price Prediction Using Prophet]”, Journal of Energy and Electrical Engineering (JEEE), Vol. 2 No 4, (2023). Available at https://jurnal.unsil.ac.id/index.php/jeee/article/view/6422 [Google Scholar]
  11. E. Setiyowati, A. Rusgiyono, Tarno, Model Kombinasi Arima dalam Peramalan Harga Minyak Mentah Dunia [Arima Combination Model in Forecasting World Crude Oil Prices]”, Jurnal Gaussian, Vol. 7, No. 1, Halaman 54–63 (2018). https://doi.org/10.14710/j.gauss.7.1.54-63, ISSN: 2339-2541, Online di: https://ejournal3.undip.ac.id/index.php/gaussian/ [CrossRef] [Google Scholar]
  12. P. Zainal, Y. Angraini, A. Rizki, “Penerapan Metode Generalized Auto-Regressive Conditional Heteroskedasticity untuk Peramalan Harga Minyak Mentah Dunia [Application of the Generalized Auto-Regressive Conditional Heteroskedasticity Method for Forecasting World Crude Oil Prices]”, Xplore, Vol. 12, No. 1, 12–21 (2023). https://doi.org/10.29244/xplore.v12i1.1096, ISSN: 2655-274412. Available at https://journal.stats.id/index.php/xploree- [CrossRef] [Google Scholar]
  13. V. Virgianti, S. Martha, N. Imro’ah “Penerapan Fuzzy Time Series Chen Average Based pada Peramalan Curah Hujan [Application of Chen Average Based Fuzzy Time Series on Rainfall Forecasting]”, Buletin Ilmiah Math. Stat. dan Terapannya (Bimaster), Vol. 10, No. 4, (2021), hal 485–494. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.