Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/27531
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dc.contributor.authorSupapakorn T.
dc.contributor.authorIntarapak S.
dc.contributor.authorVuthipongse W.
dc.date.accessioned2022-12-14T03:17:34Z-
dc.date.available2022-12-14T03:17:34Z-
dc.date.issued2022
dc.identifier.issn18140424
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85123528361&partnerID=40&md5=427541f9cb49108d363e57f863d90da0
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/27531-
dc.description.abstractThe 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.
dc.languageen
dc.titleA Decision Tree for Information of Foreign Tourists Traveling to Thailand
dc.typeArticle
dc.rights.holderScopus
dc.identifier.bibliograpycitationInternational Journal of Mathematics and Computer Science. Vol 17, No.1 (2022), p.195-206
Appears in Collections:Scopus 2022

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