Business Intelligence Model to Analyze Social Media Information
Parama Fadli Kurnia, Suharjito Suharjito · Procedia Computer Science · 2018
Social media is a platform to share information that is very liked by everyone nowadays because some of the facilities that make it easier for us to communicate with each other, share documents, chat and even create a community. In addition, we can also analyze the content of social media by using several methods in data mining, so that we can get new the information to support decision making that can bring benefits to individuals and companies. The purpose of this research, to create a business intelligence dashboard to observe the performance of each Topic or channel of news posted to social media accounts such as Facebook and Twitter. Topical performance in social media is the number of Topics in articles posted to social media getting like, share, comment etc. To be able to know the Topic of a news post in social media, used some text classification techniques such as Naive Bayes, SVM and Decision Tree. The comparative results of the algorithms are taken which has the best accuracy of SVM for subsequent implementation in the data warehouse. Meanwhile, the business intelligence dashboard data source will be sourced from the data warehouses that have been made before.