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Submitted
August 5, 2022
Accepted
April 3, 2023
Published
August 23, 2023
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Abstract

The train at this time has become one of the most popular public transportation for medium and long-distance travel. The number of train passengers is difficult to predict during the holiday season. This study aimed to predict the number of train passengers using the Seasonal Autoregressive Integrated Moving Average (SARIMA) method. The stages used in this study include (1) dataset preparation, (2) preprocessing data, and (3) experimental testing and methods. The SARIMA model obtained is ARIMA(2,1,0)(0,1,2)[12] with an AIC value of 2379,265. A diagnostic model was carried out, and it was found that the model is quite good. So the SARIMA method used in predicting passengers is accurate.

Keywords

Artificial Neural Network Method Dataset Java Island SARIMA Model Train passenger

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How to Cite
Muthoharoh, L., Dimas Wahyu Saputro, Dhea Sukma Agustiana, Fadia Dilla Sabine, Lis Nuraini, Rekzi P. Manullang, Taj Shavira, & Mika Alvionita. (2023). Predicting the Number of Train Passengers in Java Island using SARIMA Model. EKSAKTA: Journal of Sciences and Data Analysis, 4(2), 40–48. https://doi.org/10.20885/EKSAKTA.vol4.iss2.art5
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