Open AccessImplementasi Algoritma Naive Bayes Pada Data Set Kualitatif Prediksi Kebangkrutan
Author(s) -
Fakhriza Firdaus,
Ali Mukhlis
Publication year - 2020
Publication title -
jurikom (jurnal riset komputer)/jurikom
Language(s) - English
Resource type - Journals
eISSN - 2715-7393
pISSN - 2407-389X
DOI - 10.30865/jurikom.v7i1.1757
Subject(s) - naive bayes classifier , computer science , machine learning , data mining , artificial intelligence , task (project management) , probabilistic logic , process (computing) , bayes' theorem , data set , bankruptcy , set (abstract data type) , bayesian probability , engineering , support vector machine , finance , business , systems engineering , programming language , operating system
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.