PENGGUNAAN FITUR WORDCLOUD DAN DOCUMENT TERM MATRIX DALAM TEXT MINING
Musthofa Galih Pradana
Abstract
Much information and data can be extracted from social media differences, with more and more social media users. Data in 2019 states that there are 150 million users of social media in Indonesia. Based on the number of active users of social media, it can be exploited for deeper information extraction and analysis. One way that can be done is by taking comment data on social media for further processing or mining. In this research, we do data crawling and utilize the Term Document Matrix and Word Cloud features to find the most frequently written words on Facebook and Twitter social media. The words that appear most often based on the Word Cloud feature will be analyzed to infer from words written on social media. In this study the word that often appears on Facebook is the word garuda for 3621 words and on Twitter is the Indonesian word for 1572. On the Facebook platform the resulting word has a positive tendency because the topics discussed are still around airlines, while on Twitter it has a negative tendency because of the word what appears is a personal name that has a negative tendency for the company.