GDL

Journal from gdlhub / 2019-06-25 11:04:19
Oleh : Rula Amjed, Muayad Sadik Croock, Telkomnika
Dibuat : 2019-06-25, dengan 1 file

Keyword : FoT, IOT, ordinal logistic regression, scrapy, tied ranks, TripAdvisor
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/11956
Sumber pengambilan dokumen : WEB

Tourism today is one of the most important economic and social sectors in the world, which plays a prominent role in the development of countries. This importance has grown as an industry through the social media networks.In this paper, a proposed method has been introduced distinguish the main factors that impact the Frequency of Travel (FoT) among Iraq local tourists. Application (API) graphics and scrapy are utilized to collect information from TripAdvisor social network in a period of (2015-2018). The collected information are reprocessed and coded for the specified nominal data using tied rank. It is important to note that the adopted technique does not lose any data about the attribute and brings different properties beforehand obscure. Data mining ordinal logistic regression is used to extract user's behavior upon local tourism in Iraq. The expected outcome of this work is to discover out the effect of personal information and the type of places on the selection of the local touristic places in Iraq. The collected information was exploited to know the preferred local touristic trends, because there are no statistics on the number of domestic tourists in Iraq. The proposed model was used for analyzing personal information and types of preferred tourism places as a factors affecting frequency of travel in Iraq. The obtained results show the prediction of preferred touristic places by tourists in Iraq.

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