Analisa Testimonial Wisatawan Menggunakan Text Mining Dengan Metode Naive Bayes dan Decision Tree, Studi Kasus Pada Hotel-Hotel Di Jakarta - Budi Wasito (Jurnal Informatika dan Bisnis, 2014)
The ability to express the opinion of lines of text can be extremely useful, and this is a goodarea to be studied, no doubt because of the possibility of commercial value because most informationis now stored as text. In this age of the internet today many reviews, opinions, comments or opinionsare so abundant and scattered in internet media in the form of text, thus giving rise to the term oroverflow of text that can be used as the object of the new knowledge that is what is called Text Mining.Currently, Text mining is believed to have a high potential commercial value. Text Mining is a processthat aims to find the information or the latest trends previously revealed, to process and analyze largeamounts of data. In analyzing part or all unstructured text, text mining to try to associate one with theother parts of the text based on certain rules.Besides text mining is also interpreted as a data mining activities from the data in the form oftext or a document, with the aim of searching for words that can represent what is in the document so itcan be analyzed in text mining connectedness, In the processing Text Mining conducted priorTokenizing process, Filtering, Stemming, Tagging and Analyzing. Stages of the process is carried outwith the help of tools Semantria. Results semantria process tool is a classification based sentimentanalysis. After appearing classification sentiment analysis, the next step was measured by the methodof Naive Bayes and Decision Tree. Baselines to generate corresponding processed products is to ensurethe characteristics of the data related to the objectives to be achieved from the study.In the context in the field of Text Mining There are a variety of processing one of which is withProcess Mining with a focus on the classification.The processed text mining based on sentimentclassification, the region with the sequence that has the highest positive sentiment Central Jakarta(80.7%) and North Jakarta (71.2%), East Jakarta (65.1%), West Jakarta (65% ) and South Jakarta(63.8%).