@inproceedings{7cd9e58f26554633a3184924436d3015,
title = "Implementation of data mining method for classifying company application data",
abstract = "Applications or software are necessary in undertaking a business company. The more advanced a company, the more applications are used. Therefore, these applications should be checked and analyzed every time to avoid stacking applications or providing information about the lack of existing applications. Data mining methods have been widely applied in companies especially to handle large data cases. In the classification problem, data mining method works very well. Algorithms that we use to classify and predict company applications are naive bayes, decision tree, random forest and k-nearest neighbors. From the research result, we found that decision tree method with J48 algorithm is the best method with the highest accuracy value and also has the fastest time compared to other methods. The accuracy value and the execution time of decision tree method are 99.92% and 0.71 seconds respectively.",
keywords = "Application, Data Mining, Deci-sion Tree, K-Nearest Neighbors, Naive Bayes, Random Forest",
author = "Herfian Setiawan and Subriadi, {Apol Pribadi}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 5th International Conference on Science and Technology, ICST 2019 ; Conference date: 30-07-2019 Through 31-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ICST47872.2019.9166222",
language = "English",
series = "Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019",
address = "United States",
}
