PREDIKSI RETAIL SALES MOBIL TOYOTA MENGGUNAKAN METODE ARIMA (AUTOREGRESSIVE INTEGRATED MOVING AVERAGE)

Adri Arisena

Abstract


Abstrak

Penjualan mobil di Indonesia saat ini terus meningkat. Untuk melakukan perencanaan yang baik, perusahaan membutuhkan sebuah nilai prediksi penjualan agar dapat menentukan target penjualan mobil. Salah satu model prediksi yang sering digunakan untuk memprediksi sebuah data yaitu metode ARIMA (Autoregressive Integrated Moving Average). Dalam penelitian ini data yang digunakan yaitu data Retail Sales mobil Toyota dari bulan Januari 2017 sampai dengan Maret 2020. Retail Sales merupakan penjualan mobil dari dealer kepada konsumen sehingga diharapkan pabrik mobil Toyota memiliki prencanaan terhadap produksi mobil sehingga menjadi efektif dan efisien.

Kata Kunci : ARIMA, time series, Toyota, Mobil

Abstrack

Car sales in Indonesia are growing. To do good planning, the company needs a sales prediction value in order to determine the car sales target. One prediction model that is often used to predict a data is the method of ARIMA (Autoregressive Integrated Moving Average). In this study the data used is the Toyota Sales Retail data from January 2017 to March 2020. Retail Sales is a car sales from dealers to consumers, so it is hoped that the Toyota automobile factory has a preproduction to the automobile manufacturing so that it becomes effective and efficient.

Keywords : ARIMA, time series, Toyota, Car


References


Arif. (2010). Penerapan metode ARIMA dalam memprediksi temperatur udara. Retrieved November 12, 2011, from http://arifzenki.wordpress.com/2008 /08/29/penerapan-metode-arima-dalammemprediksi-temperature-udara.

Box, G.E.P., Jenkins, G.M. & Reinsel, G.C. (1994). Time series analysis forcasting and control (3rd edition). Prentice Hall, Englewood Clifs.

Makridakis, S., Wheelwright, S.C. & Hyndman, R.J. (1998). Forcasting Methods and Applications (3rd edition). United States of America: John Wiley & Sons, Inc.




DOI: https://doi.org/10.25134/ijsm.v3i1.2817

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