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Twitter Data as a Decision Tree Parameter for Analysis of Current Tourism Potential Policies
(a)Edy Subowo*, (b)Imam Rosyadi, (c) Hadwitya Handayani

(a,b,c) Informatic Management, Faculty of Engineering and Computer Science, Pekajangan Pekalongan Muhammadiyah University, Pekalongan – Indonesia

edy.subowo[at]gmail.com


Abstract

Twitter is a medium of sharing information to express opinions of user events and thoughts. In tweets related to tourist attractions, users write reviews both in terms of location access, service satisfaction, conditions and functionality of existing facilities, and shopping experiences. Twitter data is broken down based on the basic words and then grouped according to the frequency of occurrence of words. There are two groups of words, the positive review group and the negative review group. Decision tree parameters are based on the frequency of occurrence of the word, visitor data trends, and investment value of each tourist location. The results of the decision tree are ranking of potential tourism sites to be developed. 200 Twitter data were collected about tourism in Pekalongan, the highest positive reviews were lawe curug attraction with 97 tweets of positive reviews and 3 negative reviews, while from the decision tree it was found that Welo tourism was ranked first as the priority tourism development object with access value location 80%, service satisfaction 85%, facility condition and functionality 95%, and shopping experience 75% with optimistic increase of visitors by 5% / year

Keywords: Data Mining; Decision Tree

Topic: Information Engineering

Link: https://ifory.id/abstract/gCcEBtLFXwQe

Conference: 1st Borobudur International Symposium (BIS 2019)

Plain Format | Corresponding Author (Nuniek Nizmah Fajriyah)

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