TEXT MINING DOKUMEN TWEET PADA TWITTER UNTUK KLASIFIKASI KARAKTER CALON KARYAWAN

Saifudin Saifudin, Kusrini Kusrini, Hanif Al Fatta

Sari


Recruitment is a means to prepare as many workers as possible according to the requirements and qualifications expected by the organization. In recruitment one of the things that is calculated is the character of the prospective employee itself. Companies or organizations usually carry out psychological tests and interviews to get the character of prospective employees. This will make the recruitment process longer and require a lot of money. One way to find out a person's character can be done by looking at the publication of daily activities on various social media. In this study the classification of prospective employees is based on tweets found on twitter. The results of this study are grouping prospective employees based on their characters using the naïve bayes classifier algorithm. From the research that has been done naïve bayes classifier algorithm has an accuracy accuracy of an average of 52% by weighting using the term document frequency.

Keywords: Naïve Bayes Classifier, TFIDF, Character


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Referensi


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