Wednesday 24th of April 2024
 

Implementation of Data Mining in Analyzing Social Media Users Personality with Nave Bayes Classifier: A Case Study of Instagram Social Media


R. Sudrajat, M.Si., Rudi Rosadi and Harits Muhammad

Instagram is a social networking application where the users reveal a lot about themselves. This data gives contribution to big data, so the authors wanted to know what information can be retrieved on the user personality. Data mining plays an important role which aims to transform raw data into a structure that can be understood to be used furthermore. Text mining refers to the process of taking high-quality information from text, one of the classification method that can be used is Nave Bayes Classifier. In this research will be performed a desktop-based application creation using Visual Studio 2015, C# programming language, and Microsoft Access 2010. This application could classify Instagram users personality with a .csv formatted data source. Based on five factor model theory, research results concluded that 24.59% is classified as Openness to New Experiences personality, 21.5% as Conscientiousness personality, 16.22% as Extraversion personality, 21.73% as a Agreeableness personality, and 15.85% as Neuroticsm personality.

Keywords: Data Mining, Five Factor Model, Instagram, Naïve Bayes Classifier

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ABOUT THE AUTHORS

R. Sudrajat, M.Si.
Drs. R. Sudrajat, M.Si., is a lecturer at Computer Science Department (major in Information System) of Padjadjaran University.

Rudi Rosadi
Rudi Rosadi, S.Si., M.Kom,. is a lecturer at Computer Science Department (major in Information System) of Padjadjaran University.

Harits Muhammad
Harits Muhammad, studied in Informatics Engineering, Department of Computer Science Padjadjaran University since August 2012 to August 2016, and has already received his S.Kom degree.


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