Peramalan Jumlah Penumpang Kereta Api di Indonesia Menggunakan Metode Seasonal Autoregressive Integrated Moving Average (SARIMA)

  • Pramesthi Utomo UIN Sunan Ampel Surabaya
  • Aris Fanani UIN Sunan Ampel Surabaya
Keywords: Transpotation, Train Passengers, SARIMA

Abstract

Transportation is a supporter of economic life, social culture, defense, and security to politics in a country. The train is efficient and anti-traffic, where the problem to this day is congestion, especially in big cities. The number of train passengers continues to increase each year and the surge in the number of train passengers occurs on Christmas and New Year holidays so that the data is seasonal. To anticipate the surge in train passengers, forecasting is needed to predict future periods. Seasonal Autoregressive Integrated Moving Average is generally a development of the ARIMA method, which is a combination of an autoregressive and moving average, in addition, this method is specifically for data patterned seasonal, thus SARIMA is the right method for data on train passenger numbers. The purpose of this study is to predict the number of train passengers in Indonesia using the SARIMA Method and produce the best model of (1,1,2)(0,1,1)12, from this model a prediction of the total number of train passengers is obtained fire in Indonesia in 2020 was 492,230,700 passengers with MSE value is 0.046875 and MAPE value is 6.26 %.

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Published
2020-08-31
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How to Cite
Pramesthi Utomo, & Aris Fanani. (2020). Peramalan Jumlah Penumpang Kereta Api di Indonesia Menggunakan Metode Seasonal Autoregressive Integrated Moving Average (SARIMA). Jurnal Algebra, 1(1), 169-178. Retrieved from http://jurnalsaintek.uinsby.ac.id/index.php/algebra/article/view/1030
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Articles