Analisa Kepribadian Pengguna Facebook Menggunakan Algoritma Support Vector Machine

Abstrak

Technological developments are so rapidly making a lot of social media appear which one of them is Facebook. With Facebook, that users can exchange information and interact without having to meet each other. On Facebook, users can upload status without any upload restrictions. From that user's Facebook status, it can be known what kind of personality is owned by user. However, manually analyzing the personality its validity can not be unknown. From that problem we made a system that can analyze the personality of Facebook users based on the status that user once uploaded. From Facebook’s status user can be retrieved information by using Facebook API and process it using text mining. After the status already processed its grouped by  Support Vector Machine algorithm. This algorithm belongs to supervised learning and is a classification method that uses linear functions to get the better results. The output of this system is personality based on Carl Jung's theory of Extrovert and Introvert based on the status ever made before to become a benchmark by the Facebook user. From 158 Facebook’s status data obtained test result equal to 83,3% from result of comparison between system expenditure made with existing system. On black box testing, 100% of the system can be obtained according to its function. This system has been tested for its usefulness based on the results of a questionnaire on 50 Facebook users by 90.45%.