Classifying User Personality Based on Media Social Posts Using Support Vector Machine Algorithm Based on DISC Approach

Author(s):  
Anggit Dwi Hartanto ◽  
Ema Utami ◽  
Sumarni Adi ◽  
Suwanto Raharjo ◽  
Mochammad Yusa ◽  
...  
2019 ◽  
Vol 15 (2) ◽  
pp. 275-280
Author(s):  
Agus Setiyono ◽  
Hilman F Pardede

It is now common for a cellphone to receive spam messages. Great number of received messages making it difficult for human to classify those messages to Spam or no Spam.  One way to overcome this problem is to use Data Mining for automatic classifications. In this paper, we investigate various data mining techniques, named Support Vector Machine, Multinomial Naïve Bayes and Decision Tree for automatic spam detection. Our experimental results show that Support Vector Machine algorithm is the best algorithm over three evaluated algorithms. Support Vector Machine achieves 98.33%, while Multinomial Naïve Bayes achieves 98.13% and Decision Tree is at 97.10 % accuracy.


Author(s):  
Mariana C. Potcoava ◽  
Gregory L. Futia ◽  
Emily A. Gibson ◽  
Isabel R. Schlaepfer

2015 ◽  
Vol 46 ◽  
pp. 205-213 ◽  
Author(s):  
Hossein Ziaee ◽  
Seyyed Mohsen Hosseini ◽  
Abdolmajid Sharafpoor ◽  
Mohammad Fazavi ◽  
Mohammad Mahdi Ghiasi ◽  
...  

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