Prediksi Kedatangan Turis Menggunakan Algoritma Weighted Exponential Moving Average

Sherly Florencia, Alethea Suryadibrata
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引用次数: 1

Abstract

Tourism is an important factor for the development of a country. Tourism can be used as a promotion to introduce natural beauty and cultural uniqueness. Government needs to predict how many tourists will come every year to do a planning. Therefore, an application is needed to help to predict the arrival of tourists in each country. In this paper, we use Weighted Exponential Moving Average (WEMA) method to predict the arrival of tourist, tourism expenditure in the country, and departure using data from 2008 to 2018. Error measurement is calculated using the Mean Absolute Percentage Error (MAPE). The result shows that the lowest average MAPE on arrival data with span 2 is at 3.28. The lowest average MAPE on tourism expenditure data with span 2 is at 3.99%. The result shows that the lowest average MAPE on departure data with span 2 is at 3.63%.
旅游业是一个国家发展的重要因素。旅游可以作为一种推广,介绍自然美景和文化的独特性。政府需要预测每年会有多少游客来做规划。因此,需要一个应用程序来帮助预测每个国家的游客到达。本文采用加权指数移动平均(Weighted Exponential Moving Average, WEMA)方法对2008 - 2018年的旅游数据进行了入境、出境和旅游消费预测。误差测量使用平均绝对百分比误差(MAPE)计算。结果表明,在跨度为2的到达数据上,平均MAPE最低为3.28。在跨度2的旅游消费数据上,平均MAPE最低为3.99%。结果表明,在跨度为2的出发数据上,平均MAPE最低为3.63%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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