• Muhammad Azmi STMIK Syaikh Zainuddin NW Anjani
  • Amiruddin Khairul Huda MTI Universitas Amikom Yogyakarta
  • Arief Setyanto MTI Universitas Amikom Yogyakarta
Keywords: Python, Tourism, Naive Bayes Classifier.


Social media currently has an extraordinary influence in decision making, including in the tourism industry to find out the reputation and popularity of a tourist destination. At present the use and use of social media is not only limited to entertainment media but also as a medium or a place to share information both information that is considered important or not important and neglected. In this study, we utilize data scattered through Instagram posts related to tourist destinations to be used as references to find out the reputation of tourist destinations on the island of Lombok. The data used comes from Instagram with a total of 600 datasets, using three keywords namely beach, dyke and hill. The method used is the Naive Bayes Classifier which will be used to classify postings and Instagram comments by classifying into positive, negative and neutral posts to tourist destinations. The results of this study can show that the accuracy of naive bayes is 59%, while tourist attractions or tourist destinations which are categorized as popular for the beach are Kuta Beach with 85% percentage and for the Gili category that is 47% Gili Air namely, mountain Mount Rinjani with a percentage of 60%.


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How to Cite
AzmiM., Amiruddin Khairul Huda, & Arief Setyanto. (2020). PEMANFAATAN DATA INSTAGRAM UNTUK MENGETAHUI REPUTASI TEMPAT WISATA DI LOMBOK. TEKNIMEDIA: Teknologi Informasi Dan Multimedia, 1(1), 39-46.
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