Analisis Algoritma C4.5 dalam Mengukur Tingkat Kepuasan Staf terhadap Kinerja Teknisi Komputer
Article Sidebar
Main Article Content
Abstract
Article Summary
This study was conducted to determine the level of computer technician performance on staff satisfaction so that staff do not face obstacles in working so that the teaching and learning process and human resource process run effectively. By knowing the level of staff satisfaction, the academic party can easily find out the level of computer technician performance, so that if there are inappropriate results, the academic party can quickly fix and improve the performance of computer technicians. This study was conducted in measuring staff satisfaction with the performance of computer technicians at Universitas Potensi Utama. The method used by the author in this study is the C4.5 algorithm method by producing rules, accuracy values and decision trees, for the data collection process which will be carried out using a questionnaire distributed to staff via a google form link that can be assessed. The data used by the author is staff data totaling 129 respondents. The measurement results obtained using the C4.5 algorithm method are an accuracy level of 106 data with a total of 82% with the root attribute Reliability, with branch attributes namely Empathy and Tangibles. It is hoped that the results of this study can continue to be carried out periodically to improve the performance of computer technicians according to their competence so that the existing system can continue to run very well.
Keywords
Article Keywords
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC-BY 4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
License: All articles are licensed under 
Galih, G., & Eriyadi, M. (2022). Perbandingan Model NBC, SVM, dan C4. 5 dalam Mengukur Kinerja Karyawan Berprestasi Pasca Pandemi Covid-19. J. Inform, 9(2), 123-130.
Huang, H., Wang, H., & Sun, M. (2020). Incomplete data classification with view-based decision tree. Applied Soft Computing, 94, 106437. https://doi.org/10.1016/j.asoc.2020.106437.
Jannah, E., Sihombing, V., & Masrizal, M. (2023). Penerapan Data Mining Klasifikasi Kepuasan Pelanggan Transportasi Online Menggunakan Algoritma C4. 5. MEANS (Media Informasi Analisa dan Sistem), 1-7. https://doi.org/10.54367/means.v8i1.2569.
Madonsela, N. S. (2020). Integration of the management information system for competitive positioning. Procedia Manufacturing, 43, 375-382. https://doi.org/10.1016/j.promfg.2020.02.176.
Nurmala, L., Yusuf, A. S., & Sulaeman, E. (2023). Pengaruh Kualitas Pelayanan dan Persepsi Harga terhadap Tingkat Kepuasan Pelanggan Pengguna Jasa Pelayanan Driver Grab. Journal on Education, 5(2), 1950-1957. https://doi.org/10.31004/joe.v5i2.836.
Rudianto, R., Wahyudi, T., & Handayani, P. (2022). Perbandingan Akurasi C4. 5 Dan Naive Bayes Untuk Evaluasi Kinerja Karyawan Pt Catur Sentosa Adiprana. Jurnal Sistem Informasi dan Ilmu Komputer Prima (JUSIKOM PRIMA), 5(2), 61-66. https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v5i2.2350.
Rukminingsih, G. A., & Latief, M. A. (2020). Metode Penelitian Pendidikan. Penelitian Kuantitatif, Penelitian Kualitatif, Penelitian Tindakan Kelas, 53(9).
Senika, A., Rasiban, R., & Iskandar, D. (2022). Implementasi Metode Naïve Bayes Dalam Penilaian Kinerja Sales Marketing Pada PT. Pachira Distrinusa. Jurnal Media Informatika Budidarma, 6(1), 701-709.
Setiyadi, A., Novieastari, E., & Gayatri, D. (2021). Evaluation of electronic pressure injury alarm prototype based on user acceptance testing at hospital acquired pressure injury. Enfermería Clínica, 31, S432-S435. https://doi.org/10.1016/j.enfcli.2020.09.040.
Sudrajat, B. (2022). Penggunaan Algoritma C4. 5 Untuk Menentukan Kepuasan Pelanggan Pada Warnet Game Victory. Jurnal Ilmu Teknik dan Komputer, 6(1), 27.
Suherman, S., Maulana, D., & Mustikaningtyas, V. (2022). Penerapan Data Mining Untuk Klasifikasi Kepuasan Pelanggan Transportasi Online (Ojek Online) Menggunakan Algoritma C. 4.5. Prosiding Sains dan Teknologi, 1(1), 165-175.
Telaumbanua, D., & Kurniawati, I. (2022). Penerapan Algoritma C4. 5 Untuk Klasifikasi Kepuasan Pelanggan Pada Jasa Layanan Pengiriman. JoMMiT: Jurnal Multi Media dan IT, 6(1).
Vernanda, D., Piarna, R., Lustiana, H., & Apandi, T. H. (2023). Violation Types Determination of the Whistleblowing System Using the C4. 5 Algorithm. Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi, 9(1), 21-28. https://doi.org/10.24014/coreit.v9i1.22897.
Waworundeng, J. M. S., & Sandag, G. (2022). Analisis Tingkat Kepuasan Pelanggan terhadap Layanan Grab dan Gojek di Masa Pandemi Covid-19. CogITo Smart Journal, 8(1), 111-121. https://doi.org/10.31154/cogito.v8i1.395.111-121.