Forecasting Production Trafo to Get SDOH Using Seasonal ARIMA Method in PT. XYZ

Peramalan Produksi Trafo untuk Mendapatkan SDOH dengan Menggunakan Metode Seasional ARIMA di PT. XYZ

  • Muhammad Dio Dwi Septian Universitas Muhammadiyah Sidoarjo
  • Tedjo Sukmono Universitas Muhammadiyah Sidoarjo
Keywords: Forecasting, SARIMA, Inventory, Stock Day on Hand

Abstract

In the production process at PT. XYZ has a fluctuating data pattern and contains seasonality. This resulted in a reduction in the company's operational efficiency and difficulty in preparing supplies to meet uncertain demand. The method according to the demand pattern at PT. XYZ in this transformer product is the SARIMA method. The results of forecasting on transformer production at PT.XYZ gets the SARIMA(1,0,1)(1,1,1) model with influenced by the results observed at 13 weeks and errors at 14 weeks ago. The results of this forecast are used in determining the safety stock in 2021 with regard to SDOH. The SDOH planning in January 2021 will run out in 30 days with a stock plan of 838 units LV Busing so that a company policy needed to increase or decrease the stock plan if SDOH is below or above 30-35 days.

Downloads

Download data is not yet available.

References

Sogen, Markus Dwiyanto Tobi., “Analisis Pengaruh Ketidakseimbangan Beban Terhadap Arus Netral dan Losses Pada Transformator Distribusi Di PT. PLN (Persero) Area Sorong” Jurnal Electro Luceat, vol. 4, no. 1, pp. 1–10, 2018. DOI: https://doi.org/10.32531/jelekn.v4i1.80

Prahesti, Danica Dwi, Entit Puspita, Fitriani Agustina, “Peramalan Curah Hujan Kota Bandung Menggunakan Model FUngsi Transfer Multivariat Pada Deret Berkala Musiman” Eureka Matika, vol. 4, no. 1, pp. 104–118, 2016.

Sari, Ratih Kumala, “Analisis Impor Beras di Indonesia” Economics Development Analysis Journal., vol. 3, no. 2, pp. 320-325, 2014.

Rahmadayanti, Riza, Boko Susilo, Diyah Puspitaningrum, “Perbandingan Keakuratan Metode Autoregressive Integrated Moving Average (ARIMA) dan Exponential Smoothng Pada Peramalan Penjualan Semen di PT. Sinar Abadi” Jurnal Rekursif, vol. 3, no. 1, pp. 23–36, 2015.

Rahmalina, Widdya, Novreta, “Peramalan Indeks Kekeringan Kelayang Menggunakan Metode SARIMA dan SPI” Potensi, vol. 22, no. 1, pp. 64–75, 2020. DOI: https://doi.org/10.35313/potensi.v22i1.1824

Tantika, Hani Nastiti, Nanang Supriadi, Dian Anggraini, “Metode Seasonal ARIMA Untuk Meramalkan Produksi Kopi Dengan Indikator Curah Hujan Menggunakan Aplikasi R di Kabupaten Lampung Barat” Jurnal Matematika, vol. 17, no. 2, pp 49–58, 2018. DOI: https://doi.org/10.29313/jmtm.v17i2.3831

Pamungkas, Muhammad Bintang, Arief Wibowo, “Aplikasi Metode ARIMA Box-Jenkins Untuk Meramalkan Kasus DBD di Provinsi Jawa Timur,” The Indonesian Journal Public Health., vol. 13, no. 2, pp. 181–194, 2018. DOI: https://doi.org/10.20473/ijph.v13i2.2018.183-196

Maricar, M. Azman, “Analisa Perbandingan Nilai Akurasi Moving Average dan Exponential Smoothing Untuk Sistem Peramalan Pendapatan Pada Perusahaan XYZ” Jurnal Sistem dan Informatika., vol. 13, no. 2, pp. 36–45, 2015.

Masrudin, Neva Satyahadewi, Nurfitri Imro'ah, “Peramalan Jumlah Wisatawan Mancanegara di Kota Pontianak Dengan Metode Deseasonalized” Bimaster, vol. 7, no. 3, pp. 159–168, 2018.

Chusminah SM, R. Ati Haryati, Fera Nelfianti, “Efektifitas Pengelolaan Persediaan Barang Dengan Sistem Safety Stock Pada PT. X di Jakarta” Journal Economic Resources., vol. 2, no. 1, pp. 1–13, 2019. DOI: https://doi.org/10.33096/jer.v2i1.230

Published
2021-07-08
How to Cite
[1]
M. D. Dwi Septian and T. Sukmono, “Forecasting Production Trafo to Get SDOH Using Seasonal ARIMA Method in PT. XYZ”, PELS, vol. 1, no. 2, Jul. 2021.

Most read articles by the same author(s)