Implementation of data mining method for classifying company application data

Herfian Setiawan; Apol Pribadi Subriadi

doi:10.1109/ICST47872.2019.9166222

Implementation of data mining method for classifying company application data

Herfian Setiawan^*
, Apol Pribadi Subriadi

^*Corresponding author for this work

Laboratory of Information System Management

Institut Teknologi Sepuluh Nopember

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728123691
DOIs	https://doi.org/10.1109/ICST47872.2019.9166222
Publication status	Published - Jul 2019
Event	5th International Conference on Science and Technology, ICST 2019 - Yogyakarta, Indonesia Duration: 30 Jul 2019 → 31 Jul 2019

Publication series

Name	Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019

Conference

Conference	5th International Conference on Science and Technology, ICST 2019
Country/Territory	Indonesia
City	Yogyakarta
Period	30/07/19 → 31/07/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Application
Data Mining
Deci-sion Tree
K-Nearest Neighbors
Naive Bayes
Random Forest

Access to Document

10.1109/ICST47872.2019.9166222

Cite this

Setiawan, H., & Subriadi, A. P. (2019). Implementation of data mining method for classifying company application data. In Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019 Article 9166222 (Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICST47872.2019.9166222

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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",

}

Setiawan, H & Subriadi, AP 2019, Implementation of data mining method for classifying company application data. in Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019., 9166222, Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019, Institute of Electrical and Electronics Engineers Inc., 5th International Conference on Science and Technology, ICST 2019, Yogyakarta, Indonesia, 30/07/19. https://doi.org/10.1109/ICST47872.2019.9166222

Implementation of data mining method for classifying company application data. / Setiawan, Herfian; Subriadi, Apol Pribadi.
Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 9166222 (Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Implementation of data mining method for classifying company application data

AU - Setiawan, Herfian

AU - Subriadi, Apol Pribadi

PY - 2019/7

Y1 - 2019/7

N2 - 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.

AB - 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.

KW - Application

KW - Data Mining

KW - Deci-sion Tree

KW - K-Nearest Neighbors

KW - Naive Bayes

KW - Random Forest

UR - https://www.scopus.com/pages/publications/85091334606

U2 - 10.1109/ICST47872.2019.9166222

DO - 10.1109/ICST47872.2019.9166222

M3 - Conference contribution

AN - SCOPUS:85091334606

T3 - Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019

BT - Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th International Conference on Science and Technology, ICST 2019

Y2 - 30 July 2019 through 31 July 2019

ER -

Setiawan H, Subriadi AP. Implementation of data mining method for classifying company application data. In Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 9166222. (Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019). doi: 10.1109/ICST47872.2019.9166222

Implementation of data mining method for classifying company application data

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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