PERAMALAN PRODUKSI NEELAM PARFUM MENGGUNAKAN METODE SARIMA UNTUK MEMENUHI PERMINTAAN EKSPOR (STUDI KASUS: ARC USK)

Authors

  • Raihan Dara Lufika Universitas Syiah Kuala
  • Syahriza Syahriza Universitas Syiah Kuala
  • Didi Asmadi Universitas Syiah Kuala
  • Edy Fradinata Universitas Syiah Kuala
  • Friesca Erwan Universitas Syiah Kuala
  • Riski Arifin Universitas Syiah Kuala
  • Longga Nabila Universitas Syiah Kuala

DOI:

https://doi.org/10.33884/jrsi.v7i2.5505

Keywords:

Forecasting, SARIMA, Neelam Parfume, ARC USK

Abstract

The rapid development of industry in Indonesia has resulted in many companies and business actors starting to contribute to international market competition. Planning for finished product requirements is one of the important points for companies in making strategies in the business world so that companies are able to compete in the market. ARC USK is one of the leading research centers in Aceh that has produced commercial patchouli products, one of which is the Neelam Parfum product. The problem faced by ARC USK at this time is that the need for the amount of export production of Neelam Parfum itself cannot be determined with certainty, this is because ARC USK has never exported Neelam Parfum products and so far only distributes it domestically so that the amount of commercial production is only made for meet the needs of the domestic market. This study aims to create an export production schedule for Neelam Parfum using the SARIMA method and determine an implementation strategy to maximize production activities for Neelam Parfum ARC USK. Data processing is carried out using data on the number of Neelam Parfum export production targets for 2020-2021 with the help of the Eviews10 software. The validation process for forecasting is carried out using MAPE calculations. The results showed that the MAPE value was 21.334%, based on these results the forecasting of 12 periods in 2022 using the selected SARIMA model can be used and there are 9 implementation strategies that have been approved by ARC USK for export production activities of Neelam Parfum.

References

Rachman, R. (2018). Penerapan Metode Moving Average Dan Exponential Smoothing Pada Peramalan Produksi Industri Garment. Jurnal Informatika, 5(2), 211–220. https://doi.org/10.31311/ji.v5i2.3309.

Dzikrillah, N., Purba, H. H., Suwazan, D., & Noer, W. (2016). Pengendalian Persediaan Melalui Penentuan Produksi Strategi. 8(2), 169–174.

Sitorus, B. verawaty, Wahyuningsih, S., & Hayati, N. M. (2017). Peramalan dengan Metode Seasonal Autoregressive Integreted Moving Average (SARIMA) di Bidang Ekonomi (Studi Kasus: Inflasi Indonesia). 5(1), 530–532.

Risal, W. K., Puryani, P., & Nursubiyantoro, E. (2017). Perencanaan Kebutuhan Kapasitas Produksi Pada Sp Aluminium. Opsi, 10(1), 11–18. https://doi.org/10.31315/opsi.v10i1.2105.

Muhammad, A., Anggraeni, W., Si, S., & Kom, M. (2014). Implementasi Algoritma Genetika Untuk Minimasi Galat Pada Metode Peramalan Seasonal ARIMA Pada PT. XYZ. Teknik Pomits, 1(1), 1–6.

Lestari, N., & Wahyuningsih, N. (2012). Peramalan Kunjungan Wisata dengan Pendekketan Model SARIMA (Studi kasus : Kusuma Agrowisata). Jurnal Sains Dan Seni ITS, 1(Vol 1, No 1 (2012): Jurnal Sains dan Seni ITS (ISSN 2301-928X)), A29–A33. http://ejurnal.its.ac.id/index.php/sains_seni/article/view/1010/675.

Hutasuhut, A. herwindyani, Anggraeni, W., & Tyasnurita, R. (2014). Pembuatan Aplikasi Pendukung Keputusan Untuk Peramalan Persediaan Bahan Baku Produksi Plastik Blowing dan Inject. 3(2).

Dwi Septian, M. D., & Sukmono, T. (2021). Forecasting Production Trafo to Get SDOH Using Seasonal ARIMA Method in PT. XYZ. Procedia of Engineering and Life Science, 1(2). https://doi.org/10.21070/pels.v1i2.989.

Subekti, L. (2013). Implementasi Strategi Pembinaan Dan Pengembangan Koperasi Dan Usaha Kecil Menengah (Studi Pada Dinas Koperasi Dan UKM Kota Malang). Jurnal Administrasi Publik Mahasiswa Universitas Brawijaya, 1(1), 72634.

Published

2022-05-31

Issue

Section

Articles