Penerapan Metode Algoritma C4.5 Untuk Memprediksi Loyalitas Karyawan Pada PT.Tolan Tiga Indonesia Perlabian Estate

Diana Indriani Rambe, Marnis Nasution, Rahma Muti Ah

Abstract


The capital market is a place where various financial instruments are sold and bought can be long-term or short-term financial instruments. The Indonesian stock market is regulated by law No. 8 of 1995 capital market. The law clarifies the role of capital markets in the country's economy. The capital market has two functions, namely as a container for corporate financing in collecting funds from investors and as a means of investment. Loyalty is a person's loyalty in serving in a company or institution where there is a dedication and trust given by the company or institution in carrying out tasks in accordance with its expertise. in which there is a sense of love and responsibility to strive to provide the best service and behavior to show good work performance. . Loyalty is needed by companies because if employees do not have loyalty at work, it can harm the company. Thus in order to determine employee loyalty,several assessments are needed such as : employee performance,neatness in work, behavior and frequency of cooperation. Sehinnga from the assessment the company can assess how employee loyalty and if the contract employees include employees who have loyalty to the work it will be adopted as permanent employees at PT. There Are Three Types Of Indonesian Real Estate. The need for information services is very important, in predicting employee loyalty .in predicting employee loyalty can still be done manually but requires a very long processing time can be days.therefore, the author provides convenience with the use of meaching learning method, namely C4. 5 algorithm . C4.5 algorithm can facilitate the company in the process of employee prediction with just a matter of hours. So that it can make it easier for companies to determine employees who have loyalty to PT. There are three types of Indonesian real Estate.


Keywords


C4.5 Algorithm, Predicting Employee Loyalty, Data Mining.

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References


Aspita, Merlina, and Edi Sugiono(2019). Pengaruh jenjang karir, kompensasi finansial dan status karyawan terhadap kinerja karyawan Bank Rakyat Indonesia Cabang Daan Mogot.Oikonomia: Jurnal Manajemen 14.1.

Citra, Lola Melino.(2020). Pengaruh Kepemimpinan, Kepuasan Kerja Dan Motivasi Kerja Terhadap Loyalitas Karyawan. Maneggio: Jurnal Ilmiah Magister Manajemen 2.2: 214-225.

Fadlail, A. (2020). Manajemen Sdm Islami Dalam Meningkatkan Kinerja Karyawan Di Cv.Adeeva Group Jember. Al-Idarah: Jurnal Manajemen Dan Bisnis Islam, 1(1), 1–15.

Farhan hidayat zulfallah. (2022). Implementasi Algoritma Knn Dalam Mengukur Ketepatan Kelulusan Mahasiswa Uin Syarif Hidayatullah Jakarta.

Ferdiansyah, B., & Geoirmanto, L. (2020). Prediction of Loyalty in Employee Engagement to the Company Using the C4.5* Algorithm (Case Study of PT.XYZ). Journal of Information Systems and Technology (JUSTIN), 8(1), 1–11.

Ferdiansyah, B., & Geoirmanto, L. (2020). Prediction of Loyalty in Employee Engagement to the Company Using the C4.5* Algorithm (Case Study of PT.XYZ). Journal of Information Systems and Technology (JUSTIN), 8(1), 1–11.

Marentek, G. N., Pio, R. J., & Tatimu, V. (2021). Disiplin Kerja dan Loyalitas Karyawan Kaitannya Dengan Kinerja Karyawan Hotel Peninsula Manado. Jurusan Ilmu Administrasi, Program Studi Administrasi Bisnis Fakultas Ilmu Sosial Dan Politik, Universitas Sam Ratulang, 2(6).

Normah, Rifai, B., Vambudi, S., & Maulana, R. (2022). Analisa Sentimen Perkembangan Vtuber Dengan Metode Support Vector Machine Berbasis SMOTE. Jurnal Teknik Komputer AMIK BSI, 8(2), 174–180. https://doi.org/10.31294/jtk.v4i2

Pranoto, Yuliana Melita, and Reddy Alexandro Harianto(2020). "pplying the Classification Algorithm for the System Recommendations Buy Sell in Forex Trading. Jurnal Fasilkom 10.2 (2020): 152-158.

Safrizal, & Komara, P. J. (2020). Sistem Pendukung Keputusan pemberian Bonus Tahunan Karyawan dengan Metode Simple Additive Weighting (SAW) ( Studi Kasus : PT . Mega Fortris Indonesia ). Jurnal Satya Informatika, 5(1), 53–64.

Sipahutar, Y. S., Munthe, I. R., & ... (2023). Analisis Machine Learning Algoritma Regresi Linear Untuk Memprediksi Saham Di Bank Bri Di Bursa Saham Indonesia. In Jurnal Tekinkom (Teknik … (Vol. 6, Issue 8). http://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/view/747%0Ahttp://jurnal.murnisadar.ac.id/index.php/Tekinkom/article/download/747/437.

Syaefudin, A., Yusti Annasya, B., & Mutianah, M. (2022). Sistem Pendukung Keputusan Reward Karyawan Menggunakan Metode Topsis. Jurnal Insan Unggul, 10(2), 151–168. https://doi.org/10.47926/insanunggul.2022.10.2.151-168.

Syamsu, M., & Widodo. (2021). Peran Data Science dan Data Scientist Untuk Mentransformasi Data Dalam Industri 4.0. JuTech, 2(1), 27–36.

Telaumbanua, Fangatulo Dodo, et al. "Penggunaan Machine Learning Di Bidang Kesehatan." Jurnal Teknologi Dan Ilmu Komputer Prima (JUTIKOMP) 2.2 (2019): 391-399.

Widiastuti, T., Karsa, K., & Juliane, C. (2022). Evaluasi Tingkat Kepuasan Mahasiswa Terhadap Pelayanan Akademik Menggunakan Metode Klasifikasi Algoritma C4.5. Technomedia Journal, 7(3), 364–380. https://doi.org/10.33050/tmj.v7i3.1932.




DOI: https://doi.org/10.36987/informatika.v12i2.5646

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INFORMATIKA
Journal URL: https://jurnal.ulb.ac.id/index.php/informatika
Journal DOI: 10.36987/informatika
P-ISSN: 2303-2863
E-ISSN: 2615-1855

Alamat Redaksi :
Fakultas Sains dan Teknologi, Universitas Labuhanbatu
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