基于日历变化的模糊预测桑吉兰旅游人数

IF 1.2 Q3 HOSPITALITY, LEISURE, SPORT & TOURISM
W. Sulandari, Y. Yudhanto, S. Subanti, E. Zukhronah, S. Subanar, Muhammad Hisyam Lee
{"title":"基于日历变化的模糊预测桑吉兰旅游人数","authors":"W. Sulandari, Y. Yudhanto, S. Subanti, E. Zukhronah, S. Subanar, Muhammad Hisyam Lee","doi":"10.30519/ahtr.990903","DOIUrl":null,"url":null,"abstract":"Fuzzy method has been widely used in time series forecasting. However, the current fuzzy time models have not accommodated the holiday effects so that the forecasting error becomes large at certain moments. Regarding the problem, this study proposes two algorithms, extended of Chen’s and seasonal fuzzy time series method (FTS), to consider the holiday effect in forecasting the monthly tourist arrivals to ancient human Sangiran Museum. Both algorithms consider the relationship between Eid holidays as the effect of calendar variations. The forecasting results obtained from the two proposed algorithms are then compared with those obtained from the Chen’s and the seasonal FTS. Based on the experimental results, the proposed method can reduce mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) obtained from Chen’s method up to 61%, 61%, and 58%, respectively. Moreover, compared to that obtained from the seasonal FTS, the proposed method can reduce the MAE, RMSE, and MAPE values up to 35%, 36%, and 29%, respectively. The method proposed in this paper can be implemented to other time series with seasonal pattern and calendar variation effects. 1 Address correspondence to Winita SULANDARI (PhD), Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia. E-mail: winita@mipa.uns.ac.id Winita SULANDARI 1 Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0002-8185-1274 Yudho YUDHANTO Department of Informatics Engineering, Vocational School, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0001-8998-8577 Sri SUBANTI Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0002-2493-4583 Etik ZUKHRONAH Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0001-6387-4483 SUBANAR Department of Mathematics, Universitas Gadjah Mada, Yogyakarta, Indonesia ORCID: 0000-0001-7147-4471 Muhammad Hisyam LEE Department of Mathematical Sciences, Universiti Teknologi Malaysia, Johor Bahru, Malaysia ORCID: 0000-0002-3700-2363 Advances in Hospitality and Tourism Research (AHTR) An International Journal of Akdeniz University Tourism Faculty ISSN: 2147-9100 (Print), 2148-7316 (Online) Webpage: http://www.ahtrjournal.org/ Article in press","PeriodicalId":42370,"journal":{"name":"Advances in Hospitality and Tourism Research-AHTR","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2022-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting Tourist Arrivals to Sangiran Using Fuzzy with Calendar Variations\",\"authors\":\"W. Sulandari, Y. Yudhanto, S. Subanti, E. Zukhronah, S. Subanar, Muhammad Hisyam Lee\",\"doi\":\"10.30519/ahtr.990903\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fuzzy method has been widely used in time series forecasting. However, the current fuzzy time models have not accommodated the holiday effects so that the forecasting error becomes large at certain moments. Regarding the problem, this study proposes two algorithms, extended of Chen’s and seasonal fuzzy time series method (FTS), to consider the holiday effect in forecasting the monthly tourist arrivals to ancient human Sangiran Museum. Both algorithms consider the relationship between Eid holidays as the effect of calendar variations. The forecasting results obtained from the two proposed algorithms are then compared with those obtained from the Chen’s and the seasonal FTS. Based on the experimental results, the proposed method can reduce mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) obtained from Chen’s method up to 61%, 61%, and 58%, respectively. Moreover, compared to that obtained from the seasonal FTS, the proposed method can reduce the MAE, RMSE, and MAPE values up to 35%, 36%, and 29%, respectively. The method proposed in this paper can be implemented to other time series with seasonal pattern and calendar variation effects. 1 Address correspondence to Winita SULANDARI (PhD), Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia. E-mail: winita@mipa.uns.ac.id Winita SULANDARI 1 Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0002-8185-1274 Yudho YUDHANTO Department of Informatics Engineering, Vocational School, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0001-8998-8577 Sri SUBANTI Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0002-2493-4583 Etik ZUKHRONAH Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0001-6387-4483 SUBANAR Department of Mathematics, Universitas Gadjah Mada, Yogyakarta, Indonesia ORCID: 0000-0001-7147-4471 Muhammad Hisyam LEE Department of Mathematical Sciences, Universiti Teknologi Malaysia, Johor Bahru, Malaysia ORCID: 0000-0002-3700-2363 Advances in Hospitality and Tourism Research (AHTR) An International Journal of Akdeniz University Tourism Faculty ISSN: 2147-9100 (Print), 2148-7316 (Online) Webpage: http://www.ahtrjournal.org/ Article in press\",\"PeriodicalId\":42370,\"journal\":{\"name\":\"Advances in Hospitality and Tourism Research-AHTR\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2022-01-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Hospitality and Tourism Research-AHTR\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30519/ahtr.990903\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"HOSPITALITY, LEISURE, SPORT & TOURISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Hospitality and Tourism Research-AHTR","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30519/ahtr.990903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}
引用次数: 0

摘要

模糊方法在时间序列预测中得到了广泛的应用。然而,目前的模糊时间模型没有考虑假日的影响,在某些时刻预测误差较大。针对这一问题,本文提出了两种算法,即陈氏扩展法和季节模糊时间序列法(FTS),在预测桑吉兰古人类博物馆每月游客人数时考虑假日效应。两种算法都将开斋节之间的关系考虑为日历变化的影响。然后将这两种算法的预测结果与陈氏和季节FTS的预测结果进行了比较。实验结果表明,该方法可将Chen方法得到的平均绝对误差(MAE)、均方根误差(RMSE)和平均绝对百分比误差(MAPE)分别降低61%、61%和58%。此外,与季节FTS相比,该方法可将MAE、RMSE和MAPE分别降低35%、36%和29%。本文提出的方法可以应用于其他具有季节模式和日历变化影响的时间序列。1致信给Winita SULANDARI(博士),统计研究项目,Sebelas市场大学,雅加达,印度尼西亚。E-mail: winita@mipa.uns.ac.id Winita SULANDARI 1统计研究项目,印尼泗水市西比拉斯大学ORCID: 0000-0002-8185-1274 Yudho YUDHANTO印度尼西亚泗水市西比拉斯大学职业学校信息工程系ORCID: 0000-0001-8998-8577 Sri SUBANTI统计研究项目,印尼泗水市西比拉斯大学ORCID: 0000-0001-8998-8577Etik ZUKHRONAH统计研究项目,西比拉斯市场大学,印尼,苏门答腊ORCID: 0000-0001-6387-4483 SUBANAR数学系,加纳马达大学,印尼,日惹ORCID: 0000-0001-7147-4471 Muhammad Hisyam LEE马来西亚科技大学数学科学系,马来西亚,柔佛州,ORCID:酒店与旅游研究进展(AHTR) Akdeniz大学旅游学院国际期刊ISSN: 2147-9100(印刷),2148-7316(在线)网页:http://www.ahtrjournal.org/文章在出版社
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Tourist Arrivals to Sangiran Using Fuzzy with Calendar Variations
Fuzzy method has been widely used in time series forecasting. However, the current fuzzy time models have not accommodated the holiday effects so that the forecasting error becomes large at certain moments. Regarding the problem, this study proposes two algorithms, extended of Chen’s and seasonal fuzzy time series method (FTS), to consider the holiday effect in forecasting the monthly tourist arrivals to ancient human Sangiran Museum. Both algorithms consider the relationship between Eid holidays as the effect of calendar variations. The forecasting results obtained from the two proposed algorithms are then compared with those obtained from the Chen’s and the seasonal FTS. Based on the experimental results, the proposed method can reduce mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) obtained from Chen’s method up to 61%, 61%, and 58%, respectively. Moreover, compared to that obtained from the seasonal FTS, the proposed method can reduce the MAE, RMSE, and MAPE values up to 35%, 36%, and 29%, respectively. The method proposed in this paper can be implemented to other time series with seasonal pattern and calendar variation effects. 1 Address correspondence to Winita SULANDARI (PhD), Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia. E-mail: winita@mipa.uns.ac.id Winita SULANDARI 1 Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0002-8185-1274 Yudho YUDHANTO Department of Informatics Engineering, Vocational School, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0001-8998-8577 Sri SUBANTI Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0002-2493-4583 Etik ZUKHRONAH Study Program of Statistics, Universitas Sebelas Maret, Surakarta, Indonesia ORCID: 0000-0001-6387-4483 SUBANAR Department of Mathematics, Universitas Gadjah Mada, Yogyakarta, Indonesia ORCID: 0000-0001-7147-4471 Muhammad Hisyam LEE Department of Mathematical Sciences, Universiti Teknologi Malaysia, Johor Bahru, Malaysia ORCID: 0000-0002-3700-2363 Advances in Hospitality and Tourism Research (AHTR) An International Journal of Akdeniz University Tourism Faculty ISSN: 2147-9100 (Print), 2148-7316 (Online) Webpage: http://www.ahtrjournal.org/ Article in press
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Advances in Hospitality and Tourism Research-AHTR
Advances in Hospitality and Tourism Research-AHTR HOSPITALITY, LEISURE, SPORT & TOURISM-
CiteScore
2.30
自引率
17.60%
发文量
21
审稿时长
25 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信