Pengelolaan Barang Milik Negara Menggunakan Sistem Pendukung Keputusan Berbasis C5.0
Abstract
The recording of State Property at Udayana University on SIMAK-BMN has been carried out well, but the recorded State Property data only supports the preparation of balance sheets, lists of goods, reports of goods and control cards. The amount of data that is increasing every year has not been utilized optimally. The large amount of data at Udayana University and the superiority of K-Means in data grouping makes it possible to group data at the preprocessing stage using K-Means, then forming decision tree rules using C5.0 which is a refinement of the ID3 and C4.5 algorithms. The variables used in the formation of the decision tree are conditions, useful life and warranty period. The results of the study show that the decision tree rules that are formed are first checking the useful life, secondly checking good and other than good conditions, thirdly checking damaged conditions, namely lightly damaged and heavily damaged, and fourthly checking the warranty period. The recommendations generated by the decision support system are 2,894 preserved items, 1,397 deleted items, 112 maintained items with guarantees and 18 maintained items without warranty, out of a total of 4,421 items. The accuracy obtained is 97.69% calculated using the confusion matrix.
Keywords : State property; K-Means; C5.0
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References
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[25] M. Hassoon, M. S. Kouhi, M. Zomorodi-Moghadam, and M. Abdar, “Rule Optimization of Boosted C5.0 Classification Using Genetic Algorithm for Liver disease Prediction,” in 2017 International Conference on Computer and Applications (ICCA), Doha, United Arab Emirates, Sep. 2017, pp. 299–305. doi: 10.1109/COMAPP.2017.8079783.
[26] J. Guo, H. Liu, Y. Luan, and Y. Wu, “Application of Birth Defect Prediction Model Based on C5.0 Decision Tree Algorithm,” in 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Halifax, NS, Canada, Jul. 2018, pp. 1867–1871. doi: 10.1109/Cybermatics_2018.2018.00310.
[27] K. Auliasari, M. Kertaningtyas, and D. Wilis Lestarining Basuki, “Analisis Penentuan Resiko Kredit Menggunakan Algoritma C.5.0,” J-TIT, vol. 8, no. 1, pp. 28–33, 2021, doi: 10.25047/jtit.v8i1.218.
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[29] N. Agustiani, D. Suhendro, and W. Saputra, “Penerapan Data Mining Metode Apriori Dalam Implementasi Penjualan Di Alfamart,” Prosiding Seminar Nasional Riset Dan Information Science (SENARIS) 2020, vol. 2, pp. 300–304, 2020.
Published
2023-06-05
How to Cite
SUTAWAN, Pande Made; SUDARMA, Made; GUNANTARA, Nyoman.
Pengelolaan Barang Milik Negara Menggunakan Sistem Pendukung Keputusan Berbasis C5.0.
Majalah Ilmiah Teknologi Elektro, [S.l.], v. 22, n. 1, p. 125-132, june 2023.
ISSN 2503-2372.
Available at: <https://ojs.unud.ac.id/index.php/jte/article/view/97639>. Date accessed: 25 apr. 2024.
doi: https://doi.org/10.24843/MITE.2023.v22i01.P16.
Section
Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License
