车辆服务预约系统及基于ARIMA方法的人群预测特征

Q1 Social Sciences
Karto Iskandar, Bismo Asyura Widianto, Muhammad Alvito Kuntjoro, Rayhan Ardiya Dwantara, M. Herlina
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引用次数: 0

摘要

本研究首先回顾文献,以观察当前围绕车辆服务中心的问题,并使用ARIMA方法来解决类似的案例。然后,研究人员通过调查和问卷收集用户需求,进行观察过程。接下来,研究人员使用Scrum方法开发一个基于web的应用程序,该应用程序丰富了ARIMA方法。之后,研究人员通过调查和问卷来获得用户反馈,以评估用户对应用程序的体验。最后,根据问卷调查结果,平均受访者认为基于web的应用程序可以简化受访者的车辆服务预订,得分为8.85分(满分为10分)。此外,一般受访者认为基于web的应用程序可以帮助受访者规划车辆服务。通过基于web的预订应用程序上的拥挤时间预测系统,他们的排队时间更短,ARIMA模型的值为8.9分(满分10分)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vehicle service reservation system and crowd-prediction feature using ARIMA method
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.
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来源期刊
CiteScore
5.80
自引率
0.00%
发文量
163
审稿时长
8 weeks
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