KLASIFIKASI PERANGKAT KERJA DI PT. INDONESIA COMNET PLUS DENGAN METODE DECISION TREE

  • Noviyan Jati Waluyo UNISBANK SEMARANG
  • Rina Candra Noor Santi Universitas Stikubank

Abstract

  1. Indonesia Comnets Plus (ICON+) is a Subsidiary of PT. PLN (Persero) Work equipment used by employees at ICON+ is supplied from 3 different vendors. Before the work equipment is connected to the ICON+ network, standardization must be carried out by the IT team. To determine the feasibility of the equipment to be standardized by the IT team, manual checks are carried out by the IT team on duty. For those that are appropriate, standardization can be done before connecting to the network. Meanwhile, if there are work equipment that does not meet the software requirements, the user can directly contact the vendor of the work equipment provider.

To speed up the standardization process, a work device classification system is needed, using the Decision Tree C4.5 algorithm. Where device users can check independently. The results of the classification system will show the feasibility of the device to be standardized before connecting to the office network.

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References

[1] Prabowo, I. M., & Subiyanto, T. E. U. (2017). Sistem Rekomendasi Penjurusan Sekolah Menengah Kejuruan Dengan Algoritma C4. 5. Jurnal Kependidikan, 1(1), 139-149

[2] Noviandi (2021). Implementasi Algoritma Decision Tree C4.5 Untuk Prediksi Penyakit Diabetes https://digilib.esaunggul.ac.id/implementasi-algoritma-decision-tree-c45-untuk-prediksi-penyakit-diabetes-19693.html

[3] Sugara, W., & Prakoso, S. D. (2018). Penerapan Algoritma C4. 5 untuk Deteksi Dini Gangguan Autisme Pada Anak. In Seminar Nasional Teknologi Informasi Dan Komunikasi (SENTIKA) (pp. 87-96).

[4 Annas Prasetio, Muhammad Hari Hasibuan, Primatua Sitompul(2019). Simulasi Penerapan Metode Decision Tree (C4.5) Pada Penentuan Status Gizi Balita https://ojs.serambimekkah.ac.id/jnkti/article/view/2983 [4]

[5] Susanto, S., & Suryadi, D. (2010). Pengantar data mining: mengagali pengetahuan dari bongkahan data, website : http://repository.unpar.ac.id/bitstream/handle/123456789/1551/Sani_129277-p.pdf?sequence=1&isAllowed=

[6] Cynthia, E. P., & Ismanto, E. (2018). Metode Decision Tree Algoritma C. 45 Dalam Mengklasifikasi Data Penjualan Bisnis Gerai Makanan Cepat Saji. Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika), 3, 1-13.

[7] Fatmawati, K., & Windarto, A. P. (2018). Data Mining: Penerapan rapidminer dengan K-means cluster pada daerah terjangkit demam berdarah dengue (DBD) berdasarkan provinsi. CESS (Journal of Computer Engineering, System and Science), 3(2), 173-178.

[8] Mardi, Y. (2017). Data Mining: Klasifikasi Menggunakan Algoritma C4. 5. Jurnal Edik Informatika Penelitian Bidang Komputer Sains dan Pendidikan Informatika, 2(2), 213-219.

[9] Sutoyo, I. (2018). Implementasi Algoritma Decision Tree Untuk Klasifikasi Data Peserta Didik. Jurnal Pilar Nusa Mandiri, 14(2), 217-224.

[10] Andriani, A. (2012). Penerapan Algoritma C4. 5 Pada Program Klasifikasi Mahasiswa Dropout. In Seminar Nasional Matematika (pp. 139-147).
Published
2023-04-13
How to Cite
[1]
N. Waluyo and R. Noor Santi, “KLASIFIKASI PERANGKAT KERJA DI PT. INDONESIA COMNET PLUS DENGAN METODE DECISION TREE”, Jurnal Informasi dan Komputer, vol. 11, no. 01, pp. 65-72, Apr. 2023.