Prediksi Pemberian Rekomendasi Kenaikan Pangkat PNS Menggunakan Metode Naïve Bayes
- Desi Irfan Universitas Potensi Utama, Medan, Indonesia
-
Irwan Daniel
*
Universitas Potensi Utama, Medan,
Indonesia
- Adam Sagara Universitas Potensi Utama, Medan, Indonesia
- Zakarias Situmorang Universitas Potensi Utama, Medan, Indonesia (*) Corresponding Author
Abstract
A civil servant or civil servant (English: civil servant, Dutch: ambtenaar) is a person employed by a government agency to provide public services. As a profession, civil servants are positions that are pursued through career paths and not based on general elections involving the people's vote. Quoted from the Regulation of the Head of BKN No. 35 of 2011 concerning Guidelines for the Preparation of PNS Careers, the career pattern of civil servants is arranged based on the principles of certainty, professionalism, and transparency. One of the requirements to achieve the desired career is through the promotion process. The promotion or class of a civil servant cannot be separated from the recommendation of the leadership. A leader in providing recommendations must look at several important points that must be possessed by employees who will be given recommendations such as Attendance, Integrity, Cooperation and Insight or Knowledge. In the process, there are still problems in terms of technical and effectiveness because manual assessments sometimes still assess subjectively. Therefore, a study was carried out for the classification of the determination of the status of giving recommendations using the Naïve Bayes method. Naive Bayes is one method of probabilistic reasoning. The Naive Bayes algorithm aims to classify data in certain classes, then the pattern can be used to estimate the employee who will be given a recommendation, so that the leader can make a decision to give recommendation or not to the employee
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References
www.bkn.go.id.(2019). Buku Saku Kenaikan Pangkat Luar Biasa, Diakses pada 24 Januari 2022, dari https://www.bkn.go.id/wp-content/uploads/2019/11/KPLB-FIX.pdf
Dwinanta, A., & Ginting, R. (2012). Analisis Pelayanan Kenaikan Pangkat Pegawai Negeri Sipil (Studi Kasus di Kabupaten Semarang). Jurnal Ilmiah CIVIS, II(1), 173–198.
D. Nofriansyah, K. Erwansyah, and M. Ramadhan, “Penerapan Data Mining dengan Algoritma Naive Bayes Clasifier untuk Mengetahui Minat Beli Pelanggan terhadap Kartu Internet.
Panda, M., & Patra, M. R. (2007). Network Intrusion Detection Using Naïve Bayes. International Journal of Computer Science and Network Security, 7(12), 258–263. https://doi.org/10.1.1.128.936
Herlambang, A., & Wijoyo, S. (2019). Algoritma Naive Bayes untuk Klasifikasi Sumber Belajar Berbasis Teks pada Mata Pelajaran Produktif di SMK Rumpun Teknologi Informasi dan Komunikasi. Jurnal Teknologi Informasi dan Ilmu Komputer, 6(4), 430-435. doi:http://dx.doi.org/10.25126/jtiik.2019641323
Mukminin, A., & Riana, D. (2017). Komparasi Algoritma C4 . 5 , Naïve Bayes Dan Neural Network Untuk Klasifikasi Tanah. Jurnal Informatika, 4(1), 21–31.
Maulana, D., & Yahya, R. (2019). Implementasi Algoritma Naïve Bayes Untuk Klasifikasi Penderita Penyakit Jantung Di Indonesia Menggunakan Rapid Miner. Jurnal SIGMA, 10(2), 191-197
Khadafy, A. R., & Wahono, R. S. (2015). Penerapan Naïve Bayes Untuk Mengurangi Data Noise Pada Klasifikasi Multi Kelas Dengan Decision Tree. Journal of Intelligent Systems, 1(2), 136–142.
A. P. Wibawa, “Naïve Bayes Classifier for Journal Quartile Classification”, Int. J. Recent Contrib. Eng. Sci. IT, vol. 7, no. 2, pp. pp. 91–99, Jun. 2019.
Muthia, D. A. (2014). Analisis Sentimen Pada Review Buku Menggunakan Algoritma Naïve Bayes. Jurnal Paradigma, XVI(1), 8–16.
A. P. Windarto, “Implementation of Data Mining on Rice Imports by Major Country of Origin Using Algorithm Using K-Means Clustering Method,” Int. J. Artif. Intell. Res., vol. 1, no. 2, pp. 26–33, 2017.
M. G. Sadewo, A. P. Windarto, and D. Hartama, “Penerapan Datamining Pada Populasi Daging Ayam Ras Pedaging Di Indonesia Berdasarkan Provinsi Menggunakan K-Means Clustering,” InfoTekJar (Jurnal Nas. Inform. dan Teknol. Jaringan), vol. 2, no. 1, pp. 60–67, 2017.
A. Saleh, “Implementasi Metode Klasifikasi Naïve Bayes dalam Memprediksi Besarnya Penggunaan Listrik Rumah Tangga,” Citec J., vol. 2, no. 3, pp. 207–217.
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Copyright (c) 2022 Desi Irfan, Irwan Daniel, Adam Sagara, Zakarias Situmorang
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