International Journal of Data and Network Science (Jan 2023)

Vehicle service reservation system and crowd-prediction feature using ARIMA method

  • Karto Iskandar,
  • Bismo Asyura Widianto,
  • Muhammad Alvito Kuntjoro,
  • Rayhan Ardiya Dwantara,
  • Maria Grace Herlina

DOI
https://doi.org/10.5267/j.ijdns.2023.1.001
Journal volume & issue
Vol. 7, no. 2
pp. 873 – 882

Abstract

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This study begins with a literature review to observe current problems surrounding vehicle service centers and the use of the ARIMA method to resolve similar cases. Researchers then conduct the observation process by collecting user needs through surveys and questionnaires. Next, researchers use the Scrum methodology to develop a web-based application enriched with the ARIMA method. Afterward, researchers obtain user feedback using surveys and questionnaires to evaluate the user experience towards the application. Conclusively, based on the results of the questionnaires, the average respondent believes that the web-based application can simplify respondents in making vehicle service reservations with a score of 8.85 out of 10. In addition, the average respondent believes that the web-based application can assist respondents in planning vehicle service. They visit with shorter queue times through a crowded time prediction system on a web-based reservation application with the ARIMA model with a value of 8.9 out of 10.