Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/27531
Title: A Decision Tree for Information of Foreign Tourists Traveling to Thailand
Authors: Supapakorn T.
Intarapak S.
Vuthipongse W.
Issue Date: 2022
Abstract: The objective of this research is to find the influencing variables for classification of foreign tourists’ information in Thailand. The data of 400 foreign tourists were obtained from the Ministry of Tourism and Sports. By using decision tree analysis, the results show that 1) the length of stay can classify tourists by accurately predicting the expenditure per trip accounting for 76.0 % 2) age can categorize tourists with a correct prediction of travel frequency of 63.7 % 3) age, country of residence and travel arrangement can categorize tourists by accurately predicting gender accounting for 63.2 % 4) the length of stay and travel arrangement can classify tourists with 61.8% accurate predictions of the country of residence. © 2022. All Rights Reserved.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123528361&partnerID=40&md5=427541f9cb49108d363e57f863d90da0
https://ir.swu.ac.th/jspui/handle/123456789/27531
ISSN: 18140424
Appears in Collections:Scopus 2022

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