Peramalan Permintaan Produk Nata De Coco Dalam Supply Chain Management Dengan Model Arima

Authors

  • Novyta Novyta Universitas Media Nusantara Citra
  • Lutfi Alhazami Universitas Media Nusantara Citra

DOI:

https://doi.org/10.36665/theorems.v7i2.655

Keywords:

Forecasting, ARIMA

Abstract

Forecasting can be used to predict goods and services. This study aims to predict demand for nata de coco using the ARIMA model so that the company's inventory is well controlled and the supply chain is not constrained. This research data is secondary data taken during the request period from June 2021 to May 2022. The results show that the best ARIMA model is (0.2,1). The equation model formed is. Forecasting results in June 2021 are 3,104, July 2021 are 3,057, August 2021 are 3,008, September 2021 is 2,957, October 2021 is 2,906, November 2021 is 2,853, December 2021 is 2,710, January 2022 is 2,745 , February 2022 is 2,688, March 2022 is 2,631, April 2022 is 2,572 and May is 2,512.

References

Arkeman, Y., Marimin, M., & Assa, A. (2021). ANALISA KEBERLANJUTAN RANTAI PASOK AGROINDUSTRI KAKAO MENGGUNAKAN MULTI DIMENSIONAL SCALLING. Jurnal Industri Hasil Perkebunan, 16(1), 58-71.
Astuty, E. Y., & Afiatinisa, O. (2017). Rancang Bangun Sistem Peramalan Permintaan Dan Pengendalian Persediaan Manajemen Rantai Pasok Pada Olin Modiste. Jurnal Rekayasa Informasi, 6(1), 38-50,
Fahmi, F. (2020). Model Support Vector Regression (SVR) Berdimensi Tinggi dengan Pendekatan Fungsi Kernel Berbeda untuk Peramalan Harga Saham TLKM: Sebuah Pemodelan Deret Waktu Selama Masa Pandemi Covid-19. Jurnal Infomedia: Teknik Informatika, Multimedia & Jaringan, 5(2), 44-49.
Fitria, I., Alam, M. S. K., & Subchan, S. (2017). Perbandingan Metode ARIMA dan Exponential Smoothing pada Peramalan Harga Saham LQ45 Tiga Perusahaan dengan Nilai Earning Per Share (EPS) Tertinggi. Limits: Journal of Mathematics and Its Applications, 14(2), 113-125.
Manurung, R., Setiadi, A., & Mukson, M. (2021). Analisis Rantai Pasok Produk Karkas Ayam Utuh di PT Ciomas Adisatwa Unit Pabelan, Kabupaten Semarang, Jawa Tengah. Agroland: Jurnal Ilmu-ilmu Pertanian, 28(3), 278-293.
Palisungan, A., Dundu, A. K., & Willar, D. (2020). RANTAI PASOK MATERIAL DENGAN PENDEKATAN MANAJEMEN RISIKO PADA PEMBANGUNAN BANGUNAN PENGAMAN PANTAI MIANGAS. JURNAL ILMIAH MEDIA ENGINEERING, 10(2).
Pradewita, W. C., Dwidayati, N. K., & Sugiman (2021). Peramalan Volatilitas Risiko Berinvestasi Saham Menggunakan Metode GARCH–M dan ARIMAX–GARCH. Indonesian Journal of Mathematics and Natural Sciences. 44(1), 12-21.
Priyadi, D., & Mardhiyah, I. (2021). Model Autoregressive Integrated Moving Average (Arima) Dalam Peramalan Nilai Harga Saham Penutup Indeks LQ45. Jurnal Ilmiah Informatika Komputer, 26(1), 78-94.
Putri, F. T. A., Zukhronah, E., & Pratiwi, H. (2021). Model ARIMA-GARCH Pada Peramalan Harga Saham PT. Jasa Marga (Persero). Business Innovation and Entrepreneurship Journal, 3(3), 164-170.
Rezaldi, D. A., & Sugiman, S. (2021, February). Peramalan Metode ARIMA Data Saham PT. Telekomunikasi Indonesia. In PRISMA, Prosiding Seminar Nasional Matematika (Vol. 4, pp. 611-620).
Saptaria, L. (2016). Peramalan permintaan produk cincau hitam dalam memaksimalkan SCM (supply chain management). JMK (Jurnal Manajemen dan Kewirausahaan), 1(3), 247-256.

Downloads

Published

2022-07-28