Open Access
| Issue |
BIO Web Conf.
Volume 146, 2024
2nd Biology Trunojoyo Madura International Conference (BTMIC 2024)
|
|
|---|---|---|
| Article Number | 01052 | |
| Number of page(s) | 6 | |
| Section | Dense Matter | |
| DOI | https://doi.org/10.1051/bioconf/202414601052 | |
| Published online | 27 November 2024 | |
- Andriati And R. T. Wahjudi, Society’s acceptance level of herb as alternative to modern medicine for lower, middle, and upper class group, Masyarakat, Kebudayaan Dan Politik, 29, 3, 133–145 (2016) [CrossRef] [Google Scholar]
- Ekna Satriyati, Menjaga tradisi minum jamu madura dengan penyampaian pesan interpersonal kesehatan antara peramu dan pengguna, DIMENSI, 10, 2, 24–35 (2017) [Google Scholar]
- A. Saputro And B. Purwanggono. Peramalan perencanaan produksi semen dengan metode exponential smoothing pada PT. Semen Indonesia. Industrial Engineering Online Jurnal, 5. 4. 1–7 (2016) [Google Scholar]
- A. D. Mahardika And N. Susanto, Peramalan perencanaan produksi terak dengan metode exponential smoothing with trend pada PT Semen Indonesia (Persen)) Tbk.” Industrial Engineering Online Journal, 6, 1, 1–10 (2017) [Google Scholar]
- Ilyas A. Prakoso, Kusnadi, And B. Nugraha, Peramalan penjualan produk dengan metode regresi linear dan aplikasi POM-QM Di PT XYZ, Scientific Journal Widya Teknik, 21, 1, 14–20 (2022) [CrossRef] [Google Scholar]
- P. R. Winters, Forecasting sales by exponentially weighted moving averages, Manage Sci, 6, 324–342, (1960), https://Api.Semanticscholar.Org/Corpusid:154867353 [CrossRef] [Google Scholar]
- M. Atwani, M. Hlyal, And J. Elalami, A Review Of Artificial Intelligence Applications In Supply Chain, in ITM Web Of Conferences (2022), https://Api.Semanticscholar.Org/Corpusid:249445047 [Google Scholar]
- F. Layla Sari, Demand Forecasting Of Trading Companies Based On Time Sequence (2021) [Google Scholar]
- S. Mukhopadhyay, A. O. Solis, And R. S. Gutierrez, The accuracy of non-traditional versus traditional methods of forecasting lumpy demand, J Forecast, 31, 8, 721–735 (2012), doi: 10.1002/For.1242. [CrossRef] [Google Scholar]
- Nisa Ayunda, Faizah, And Sujarwo, Analisa Peramalan Data Time-Series Dengan Aplikasi Windows POM-QM,” Buana Matematika: Jurnal Ilmiah Matematika Dan Pendidikan Matematika, 11, 2, 167–180 (2021), doi: 10.36456/Buanamatematika.V11i2.5913. [CrossRef] [Google Scholar]
- S. Hartini, Teknik mencapai produksi optimal (Lubuk Agung, Bandung, 2011) [Google Scholar]
- J. Heizer and B. Render, Manajemen operasi: manajemen keberlangsungan dan rantai pasokan edisi ke-11 (Salemba Empat, 2015) [Google Scholar]
- V Gaspersz, Production planning and inventory control (Gramedia Pustaka Utama, 1998) [Google Scholar]
- E. Heriansyah and S. Hasibuan, Implementasi Metode Peramalan Pada Permintaan Bracket Side Stand K59A, Jurnal PASTI, 12, 2, 209–223 (2018) [Google Scholar]
- D. Ratna Kania, S. Putri Lestari, B. Barlian, P. Studi Manajemen, F. Ekonomi and Bisnis, And U. Perjuangan Tasikmalaya, Penerapan Metode Peramalan Moving Average Dan Exponential Smoothing UntukMenyusun Perencanaan Produksi (Survei Pada UMKM Pembuatan Bordir Dan Pakaian, Nining Collection Di Ciamis), Jurnal Ilmiah Multidisiplin, 1, 10, 3609–3622 (2022) [Google Scholar]
- I. Setiawan, Rancang bangun aplikasi peramalan persediaan stok barang menggunakan metode Weighted Moving Average (WMA) pada toko barang XYZ (2021) [Google Scholar]
- N. P. L. Santiari And I. G. S. Rahayuda, Penerapan Metode Exponential Smoothing Untuk Peramalan Penjualan Pada Toko Gitar, JOINTECS (Journal Of Information Technology And Computer Science), 5, 3, P.203 (2020) doi: 10.31328/Jointecs.V5i3.1520. [CrossRef] [Google Scholar]
- N. Ayunda, Faizah, And Sujarwa, Analisa peramalan data time-series dengan aplikasi windows POM-QM, Jurnal Ilmiah Matematika dan Pendidikan Matematika, 11, 2 (2021) [Google Scholar]
- A. Abrami, A. Y. Aravkin, And Y. Kim, Time series using exponential smoothing cells, Jun (2017), http://arxiv.org/abs/1706.02829 [Google Scholar]
- C. C. Holt, Forecasting seasonals and trends by exponentially weighted moving averages, Int J Forecast, 20, 1, 5–10 (2004), doi: Https://Doi.Org/10.1016/J.Ijforecast.2003.09.015. [CrossRef] [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.