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All Journal EKSAKTA: Journal of Sciences and Data Analysis Journal of Science and Applicative Technology Jurnal Matematika UNAND Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Journal of Science and Technology Journal of Fundamental Mathematics and Applications (JFMA) Smart Society: Community Service and Empowerment Journal Indonesian Journal of Applied Mathematics
Mika Alvionita Sitinjak
Institut Teknologi Sumatera
Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Other

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Journal : EKSAKTA: Journal of Sciences and Data Analysis

 1 
Predicting the Number of Train Passengers in Java Island using SARIMA Model Luluk Muthoharoh; Dimas Wahyu Saputro; Dhea Sukma Agustiana; Fadia Dilla Sabine; Lis Nuraini; Rekzi P. Manullang; Taj Shavira; Mika Alvionita
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 4, ISSUE 2, August 2023
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol4.iss2.art5

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.
Co-Authors Danni Gathot Harbowo Dhea Sukma Agustiana Dimas Wahyu Saputro Fadia Dilla Sabine Fuji Lestari Irawati, Febri Dwi Lis Nuraini Luluk Muthoharoh Muliawati Muliawati, Triyana Muthoharoh, Luluk Nadeak, Christyan Tamaro Nuramaliyah, Nuramaliyah Rahwani, Putri Hazizah Rekzi P. Manullang Riri Lestari Satria, Ardika Syaiful, Achmad Taj Shavira Tirta Setiawan, Tirta