ID3 Algorithm Analysis to Determine Employee Performance Levels
Adek Santika Sari, Ibnu Rasyid Munthe, Angga Putra Juledi
Abstrak
The ID3 method is used in this study to evaluate the level of employee performance at PT. Ayu Septa Perdana. The resulting decision tree shows that the initiative factor is the main determinant of employee performance. Employees who have initiative tend to show good performance, with a success rate of 96.3%. This shows that initiative is a very important quality in this work environment, because it can lead employees to better performance. In contrast, employees who do not have initiative are further assessed based on their level of discipline, indicating that management considers discipline as a secondary factor in determining the quality of performance. If an employee does not have initiative, the decision tree shows that discipline is the next factor taken into account. Employees who have a discipline value higher than 27 tend to be categorized as having “Poor” performance, with a percentage error of 100%. However, for employees who have a discipline value of 27 or less, there is a 66.7% chance that their performance is still good, even though they do not have initiative. This confirms that although initiative is the main factor, discipline still plays an important role in evaluating employee performance. Thus, this decision tree not only assesses the quality of work but also helps identify areas of improvement for employees who are considered less good. The purpose of using the ID3 method in this study is to develop a model that is able to classify and predict employee performance levels accurately. With an accuracy of 89%, this model is quite reliable in providing insight to management about important factors that affect performance. By knowing the main factors such as initiative and discipline, companies can design more focused training and development programs to improve overall employee performance. This finding is expected to provide a positive contribution in human resource management and assist in more effective decision making in the future.
Keywords
Classification; Data Mining; ID3 Method
Full Text
Referensi
[1] Z. Putra and M. Muzakir, “Survei Kepuasan Masyarakat Atas Pelayanan Administrasi di Kantor Desa: Studi Komparasi Menggunakan Uji One Way Anova dan Analisis Indeks Kepuasan Masyarakat,” J. Bisnis Dan Kaji. Strateg. Manaj., vol. 6, no. 2, pp. 186–200, 2022, doi: 10.35308/jbkan.v6i2.6405.
[2] N. Noviarni and M. Rianthy, “Pengaruh Pemberian Insentif Dan Motivasi Kerja Terhadap Kinerja Karyawan Pt. Margi Wahyu Cabang Palembang,” J. Kompetitif, vol. 11, no. 1, pp. 22–28, 2022, doi: 10.52333/kompetitif.v11i1.896.
[3] N. Annaastasia, A. Mansyur, N. A, and A. Siddiq, “Peningkatan Informasi Larangan dan Ancaman Terhadap Penangkapan dan Perdagangan Penyu Sebagai Sumberdaya Ikan yang Dilindungi Melalui Media Poster Di Desa Lalowaru Kecamatan Moramo Utara dan Desa Ranooharaya Kecamatan Moramo,” J. Pengabdi. Magister Pendidik. IPA, vol. 5, no. 4, pp. 146–149, 2022, doi: 10.29303/jpmpi.v5i4.2330.
[4] M. Ekhsan and R. Mariyono, “Pengaruh Gaya Kepemimpinan Islami, Budaya Organisasi Islami dan Insentif terhadap Produktivitas Kerja Karyawan PT Yanmar Indonesia,” Jesya (Jurnal Ekon. Ekon. Syariah), vol. 3, no. 2, pp. 265–275, 2020, doi: 10.36778/jesya.v3i2.188.
[5] K. Ma, “Analisis Penerapan Algoritma ID3 dalam Mendiagnosis Kesuburan Pria,” 2019.
[6] S. Nurajizah, “Operator Bagging Dalam Mendiagnosa Kesehatan,” vol. 6, no. 2, pp. 92–96, 2021.
[7] A. P. Natasuwarna, “Seminar Pendekatan Data Mining Memprediksi Profil Sosial Masyarakat Menggunakan Aplikasi RapidMiner,” Semin. Nas. Pengabdi. Masy., vol. 38, pp. 38–44, 2019.
[8] K. Pustaka, “PENERAPAN ALGORITMA DECISION TREE ID3 UNTUK PREDIKSI KELULUSAN MAHASISWA JENJANG PENDIDIKAN D3 DI FAKULTAS TEKNIK,” vol. 5, no. 2, pp. 2–6, 2019.
[9] B. G. Sudarsono, R. Saputra, F. Utomo, and C. Wijaya, “Segmentasi Popularitas Akun Youtube Menggunakan Metode ID3,” JBASE – J. Bus. Audit Inf. Syst., vol. 3, no. 2, pp. 32–38, 2020, doi: 10.30813/jbase.v3i2.2269.
[10] L. Irawan and L. H. Hasibuan, “ANALISA PREDIKSI EFEK KERUSAKAN GEMPA DARI MAGNITUDO ( SKALA RICHTER ) DENGAN METODE ALGORITMA ID3 MENGGUNAKAN APLIKASI DATA,” vol. 14, no. 2, pp. 189–201, 2020.
[11] S. M. P. N. R. Selatan, “Penerapan Data Mining dalam Menganalisa Pola Kelayakan Siswa Pada Kelas Unggulan Menggunakan Algoritma Iterative Dichotomiser 3 ( ID3 ) pada,” vol. 18, no. 2, pp. 154–160, 2019.
[12] “Penerapan metode id3 untuk memprediksi pencapaian hasil penjualan pada toko eli skripsi,” p. 2021, 2021.
[13] A. P. Sulaiman, L. Liliana, and L. W. Santoso, “Kecerdasan Buatan dengan Metode ID3 Finite State Machine dalam Turn-Based Tactics Game,” J. Infra, no. 031, 2021, [Online]. Available: http://publication.petra.ac.id/index.php/teknik-informatika/article/viewFile/11421/10031
[14] M. Aritonang, “Penerapan Algoritma ID3 dalam Prediksi Kebutuhan Pupuk,” vol. 2, no. 4, pp. 247–253, 2021.
[15] A. Kepuasan, K. Menggunakan, and C. Algoritma, “Analisa Kepuasan Konsumen Menggunakan Algoritma C4.5,” no. September, pp. 126–131, 2020.