Forecasting Model Of Arabica Coffee Export Demand With Decomposition Method On CV. Gayo Coffee Oro

Syarifah Akmal, M Sayuti, Muhariani Hasibuan

Abstract


Coffee is one type of plant that has a harvest season in certain months, while the amount of coffee export demand is always there even though it is not in the coffee season. So that the company is often unable to meet the demand for coffee exports. This study aims to find out how the use of the decomposition method in forecasting the demand for Arabica coffee exports and also to find out the results of forecasting the demand obtained. This study uses a quantitative approach, which was conducted at CV. Oro Kopi Gayo is located in the Gayo highlands, precisely in the Mongal Village, Bebesen District, Central Aceh Regency. The data used in this study is secondary data, namely data on Arabica coffee export demand from 2017 to 2021. The results of forecasting coffee export demand using the decomposition method in 2022, which is 1754216 kg, have increased when compared to demand in 2021, which is equal to 1536000 kg with a percentage increase of 14%. Demand for coffee exports in January was 160192 kg, February was 172445 kg, March was 146829 kg, April was 76822 kg, May was 88583 kg, June was 106127 kg, July was 129510 kg, August was 45472 kg, September was 45472 kg 269457 kg, October 225509 kg, November 239090 kg, and December 94090 kg. The highest demand for Arabica coffee exports occurred in September, amounting to 269457 kg, in November at 239090 kg, and in October at 225509 kg. Then it decreased again in December, which was 94090 kg. The increase and decrease in the repetitive data pattern indicate that the data has a seasonal pattern.


Keywords


Decomposition, Arabica, Forecasting, Export

Full Text:

PDF

References


J. . Heizer, Manajemen Operasi. Jakarta: Salemba Empat, 2015.

P. Subagyo, Forecasting: Konsep Dan Aplikasi. Yogyakarta: Bpfe Ugm., 1986.

D. C. Frechtling, Forecasting Tourism Demand: Methods And Strategies. Uk: Butterworth-Heinemann. Oxford, 2001.

Sumayang, “Enhanced Reader,” 2003.

V. Gasperz, Production Planningand Inventory Control. Jakarta: Gramedia, 2004.

M. I. Baidowi And E. A. Buniarto, “Analisis Ramalan Penjualan Menggunakan Metode Time Series Dalam Menentukan Jumlah Produksi M . Imam Baidowi Edwin Agus Buniarto Abstrak,” J. Ekononomi Manaj., Vol. 1, No. 1, Pp. 33–41, 2020.

J. Heizer And R. Barry, Menejemen Operasi, 9th Ed. Jakarta: Salemba Empat, 2009.

E. Indriastiningsih, A. Oktaviana, And T. Devi, “Analisis Forecasting ( Peramalan ) Produk Keripik Pisang Kemasan Bungkus ( Studi Kasus : Home Industry-Keripik Pisang Surakarta),” J. Gaung Inform., Vol. 9, Pp. 129–139, 2016.

A. H. Nasution, Manajemen Industri. Yogyakarta: Andi Offset, 2006.

D. K. Sofyan, Perencanaan & Pengendalian Produksi. Yogyakarta: Graha Ilmu, 2013.

Santoso, Peramalan Rata - Rata. Jakarta: Rineka Cipta, 2009.

Makkulau, R. Raya, And S. Marlinda, “Aplikasi Metode Dekomposisi Pada Peramalan Jumlah Kelahiran,” Semin. Nas. Teknol. Terap. Berbas. Kearifan Lokal, Vol. 1, No. 1, Pp. 535–545, 2018.

B. . Bowerman, R. . O’connell, And A. . Koehler, Forecasting, Time Series And Regresion. South-Western: Thomson Brooks/ Cole, 2005.

Spyros Makridakis, Metode Dan Aplikasi Peramalan, 1st Ed. Jakarta: Erlangga, 1993.

B. Abraham And Ledolter Johanes, Statistical Methods For Forcasting. New York: John Wiley & Suns, 1983.

F. C. Kadoena And L. Handayani, “Metode Dekomposisi Multiplikatif Rata-Rata Bergerak Untuk Peramalan Tingkat Produksi Padi Ladang Sulawesi Tengah ( Moving Average Multiplicative Decomposition Method For Forecasting The Level Of Field Rice Production In Central Sulawesi ),” Vol. 08, Pp. 99–105, 2019.

H. Cipta, “Model Peramalan Volume Pengunjung Taman Rekreasi The Leu Garden,” Vol. 5, No. 1, Pp. 1–14, 2020.

M. Marine, Keristina Br. Ginting, And Ariyanto, “Peramalan Jumlah Penumpang Pesawat Dengan Menggunakan Metode Dekomposisi (Studi Kasus: Unit Penyelenggara Bandar Udara (Upbu) Kelas Ii Frans Seda Maumere),” Vol. 01, No. November 2019, 2022.

D. I. Ulya, Airlangga, And Mahmudah, “Decomposition Method For Forecasting The Number Of,” Vol. 9, No. July, Pp. 36–43, 2020, Doi: 10.20473/Jbk.V9i1.2020.36.

R. Dwi Cahyani, “Peramalan Permintaan Golongan Darah A , B , O Dan Ab Dengan Metode Exponential Smoothing Dan Metode Dekomposisi Di Utd Pmi Kota Malang Oleh : Renanda Dwi Cahyani Fakultas Ekonomi Dan Bisnis Universitas Brawijaya Dosen Pembimbing : Abstrak : Kondisi Kekura,” 2018.




DOI: https://doi.org/10.52088/ijesty.v2i3.282

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Syarifah Akmal, M Sayuti, Muhariani Hasibuan

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

International Journal of Engineering, Science and Information Technology (IJESTY) eISSN 2775-2674