Prediksi Kepribadian Mahasiswa Menggunakan Naïve Bayes
DOI:
https://doi.org/10.33884/psnistek.v5i.8056Keywords:
Personality, predictions, Naïve BayesAbstract
College students are in a transitional phase from youth to adulthood. The transition period makes students still unstable to control their emotions. It makes his curiosity towards new things increase which then shows his personality traits. The purpose of this study was to find out how researchers collect data about personality from students, to find out how to classify personality from the data that has been collected. Research methods start from collecting data using Text Preprocessing questionnaires, Data Training, Classification, Testing, to making predictions. After applying the classification algorithm with the Naïve Bayes algorithm, the Train Score is 0.947 and the Test Score is 0.879. Trials have also been carried out to make predictions with new data whose results are correct.
References
D. M. Alam, A. T. D. Prabowo, A. Prabono, And M. W. Pratama, “Klasifikasi Karakteristik Kepribadian Mahasiswa Universitas Amikom Yogyakarta Dengan Menggunakan Metode Naive Bayes,” Pp. 17–28, 2020.
Fitriana, Frizka (2021) Analisis Sentimen Opini Terhadap Vaksin Covid-19 pada Media Sosial Twitter Menggunakan Support Vector Machine dan Naive Bayes. Jurnal Komtika (Komputasi dan Informatika) Vol. 5 No. 1 2021
Fahrudy. D, dkk. 2022. Intelligent System For Classification Of Student Personality With Naive Bayes Algorithm. SINTECH JOURNAL E-ISSN 2598-9642 Vol. 5 No 1 – April 2022
Krisdiyanto, Taofik (2021). Analisis Sentimen Opini Masyarakat Indonesia Terhadap Kebijakan PPKM pada Media Sosial Twitter Menggunakan Naïve Bayes Clasifiers, Journal CorelT. Vol 7, No.1 2021
Liu L., Preotiuc-Pietro D., Samani Z. R., Moghaddam M. E, Ungar L. H., Analyzing Personality through Social Media Profile Picture Choice. In Tenth international AAAI conference on web and social media (ICWSM), 2016, 211-220.
Tadhan and F. R. Purba, “Aplikasi tes personality plus berbasis web,” vol. Vol. 01 No, pp.327–337, 2022.
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