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":"1 1","pages":""},"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. 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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. 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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