Implementasi Algoritma Naive Bayes Pada Data Set Kualitatif Prediksi Kebangkrutan
DOI:
https://doi.org/10.30865/jurikom.v7i1.1757Keywords:
Data Mining, Classification, Naive BayesAbstract
A number of studies about bankruptcy prediction have widely applied the Data Mining technique to find useful knowledge automatically based on an assessment of the management's assessment of the risks that exist in a company. In the process of risk assessment the actual knowledge of experts is still considered an important task because the predictions of experts depend on their effectiveness. This study aims to extract information from qualitative bankruptcy data sets so that they can be used as a useful learning resource for improving the management of a company. The technique used in this study is classification using the Naive Bayes algorithm. Naive Bayes uses probabilistic predictions to classify data.
References
Dr.M.Handi Shubhan., SH., MH., M.Si, Hukum Kepailitan. Kencana, 2015.
L. Muflikhah, D. E. Ratnawati, dan R. R. MP, Data Mining. Universitas Brawijaya Press, 2018.
E. luthfi dan U. Amikom, Algoritma Data Mining. Penerbit Andi.
S. Adinugroho dan Y. A. Sari, Implementasi Data Mining Menggunakan Weka. Universitas Brawijaya Press, 2018.
S. GarcÃa, J. Luengo, dan F. Herrera, Data Preprocessing in Data Mining. Springer International Publishing, 2014.
