利用网络搜索数据对巴厘岛航空旅客外流的短期预测

Parma Dwi Widy Oktama
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引用次数: 0

摘要

航空旅客已成为交通运输部门的战略指标之一。由于印尼统计局(BPS)公布的官方数据滞后30天,因此无法实时了解该指标的情况。利用近年来快速发展的网络搜索数据,本研究旨在探索利用网络搜索数据进行短期预测的可能性,以便更早地了解指标的总体前景。基于这项研究,网络搜索数据和官方统计数据显示出强烈的相关性,并且随着时间的推移具有相似的移动模式。将网络搜索数据作为预测因子应用于时间序列建模,特别是时间序列回归和自回归模型(SARIMA和SARIMAX),得到的预测值很好地接近响应变量的实际值。此外,还证明了使用网络搜索数据可以提高模型的准确性。SARIMAX模型分析结果显示,2021年9月和10月巴厘岛航空旅客流出数量普遍高于2021年8月。航空旅客人数的增加被认为是由于新冠肺炎病例的减少,这引发了公众对旅行的信心再次上升。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-Term Forecasting of Air Travellers Outflows from Bali Using Web Search Data
Air travelers have become one of the strategic indicators in the transportation sector. The official data-released by Statistics Indonesia (BPS) for thirty days-lag, makes the condition of this indicator can’t be known in real-time. By the utilization of web search data that has been briskly evolving in recent years, this study aims to explore the possibility of using web search data in performing short-term forecasting to know the general outlook of the indicator earlier. Based on this study, web search data and official statistics figures show a strong correlation and having similar movement patterns over time. The application of web search data as a predictor in time series modeling, especially on time series regression and autoregressive model (SARIMA and SARIMAX), turn out a predicted value that well-approach the actual value of the response variable. In addition, it is proven that the use of web search data can increase model accuracy. The analysis results using SARIMAX model shows that the number of air traveller’s outflows from Bali in September and October 2021 will generally be higher than the number in August 2021. The increasing number of air travelers is thought due to a decrease in Covid-19 cases which has triggered the public's confidence in travelling about to rise again.
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