COMPARISON IN PREDICTING THE SHORT-TERM USING THE SARIMA, DSARIMA AND TSARIMA METHODS

  • Muhammad Giovani Mathematics Study Program, Department of Mathematics and Information Technology, Kalimantan Institute of Technology
  • Indira Anggriani Mathematics Study Program, Department of Mathematics and Information Technology, Kalimantan Institute of Technology
  • Syalam Ali Wira Dinata Simatupang Statistics Study Program, Department of Mathematics and Information Technology, Kalimantan Institute of Technology
DOI: https://doi.org/10.30598/barekengvol16iss4pp1487-1496
Keywords: Seasonal, ARIMA, Big Data, Forecasting

Abstract

The flow of data and information is growing rapidly and rapidly in various sizes and means which is called Big Data. In the face of a change for the better in the future, a careful analysis and design of a data processing system is needed, in which a predictive framework can formulate the right policy to be one of the efforts to make a good decision. This is one of the appropriate Big Data processing efforts, which can be realized through one of the methods, namely prediction or forecasting is an effort to predict future values or trends as a reference for analyzing conditions in the past. One example of Big Data in the City of Balikpapan, namely the temperature within 2 meters obtained from the NASA satellite published on the website power.larc.nasa.gov. One of the methods used in this research is the ARIMA method and it is developed according to the data used. Based on the data to be used, namely temperature data within a distance of 2 meters in the city of Balikpapan, the development of data processing is carried out to pay attention to three seasonal patterns or the so-called Triple Seasonal ARIMA model. In this study, it can be seen how to build the Triple Seasonal ARIMA model and comparison with alternative models, namely Seasonal ARIMA and Double Seasonal ARIMA, and can see how the results of the Triple Seasonal ARIMA model accuracy when compared with alternative models. The method used in this study is the Seasonal ARIMA, Double Seasonal ARIMA and Triple Seasonal ARIMA methods. The results obtained in this study obtained a comparison of methods in making predictions with a specified time span, the results obtained from the Seasonal ARIMA model that it was very good at predicting a time span of 2 weeks, Double Seasonal ARIMA for a period of 1 month, Double Seasonal ARIMA for a period of 3 months, and Triple Seasonal ARIMA for a period of 6 months.

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Published
2022-12-15
How to Cite
[1]
M. Giovani, I. Anggriani, and S. A. Simatupang, “COMPARISON IN PREDICTING THE SHORT-TERM USING THE SARIMA, DSARIMA AND TSARIMA METHODS”, BAREKENG: J. Math. & App., vol. 16, no. 4, pp. 1487-1496, Dec. 2022.
Issue
Vol 16 No 4 (2022): BAREKENG: Journal of Mathematics and Its Applications
Section
Articles

Copyright (c) 2022 Muhammad Giovani, Indira Anggriani, Syalam Ali Wira Dinata Simatupang

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