Penerapan Algoritma Naive Bayes pada Penentuan Kelayakan Calon Tenaga Kerja Indonesia

Winda Hana Purba, Poningsih Poningsih, Dedi Suhendro, Irfan Sudahri Damanik, Ilham Syahputra Saragih

Abstract


Indonesian Manpower is a potential that is a huge potential for the progress of the country. However, the difficulty of employment and the high unemployment rate in Indonesia requires that some people seek perfect employment abroad, in order to improve economic levels. The lack of selection resulted in many problems in the workforce, the low level of education of prospective migrant workers resulted in them having an easy risk on other party tricks, non-violence, unpaid salaries and so on. In accordance with what has been surveyed, it turns out that the sending of these workers is actually not feasible, given the level of education, skills and abilities that are lacking for employment abroad. This study aims to facilitate the government or companies engaged in the field to channel selected workers using the Naive Bayes Method.

Full Text:

PDF

References


Syarli and A. A. Muin, “Metode Naive Bayes Untuk Prediksi Kelulusan ( Studi Kasus : Data Mahasiswa Baru Perguruan Tinggi ),” J. Ilm. Ilmu Komput., vol. 2, no. 1, p. 5, 2016.

C. Fadlan, S. Ningsih, and A. P. Windarto, “PENERAPAN METODE NAÏVE BAYES DALAM KLASIFIKASI KELAYAKAN KELUARGA PENERIMA BERAS RASTRA,” JUTIM, vol. 3, no. 1, pp. 1–8, 2018.

Asrul Ashari, Studi, P., Informatika, T., Muin, Studi, P., & Informasi, S. (2016). Metode Naive Bayes Untuk Prediksi Kelulusan ( Studi Kasus : Data Mahasiswa Baru Perguruan Tinggi ), 2(1).

Hendini, A. (2016). PEMODELAN UML SISTEM INFORMASI MONITORING PENJUALAN DAN STOK BARANG (STUDI KASUS: DISTRO ZHEZHA PONTIANAK), IV(2), 107–116.

Manalu, E., Sianturi, F. A., & Manalu, M. R. (2017). PENERAPAN ALGORITMA NAIVE BAYES UNTUK MEMPREDIKSI JUMLAH PRODUKSI BARANG BERDASARKAN DATA PERSEDIAAN DAN JUMLAH PEMESANAN PADA CV . PAPADAN MAMA PASTRIES, 1(2).

Mardi, Y. (2016). Jurnal Edik Informatika Data Mining : Klasifikasi Menggunakan Algoritma C4 . 5. Jurnal Edik Informatika. Jurnal Edik Informatika, V2.i2, 213–219. Retrieved from algorithm; classification; c-4.5

Metisen, B. M., & Sari, H. L. (2015). Analisis Clustering Menggunakan Metode K-Means dalam Pengelompokkan Penjualan Produk pada Swalayan Fadhila. Jurnal Media Infotama, 11(2), 110–118.

Nurhadi, A. (2015). Klasifikasi Konten Berita Digital Bahasa Indonesia Menggunakan Support Vector Machines ( SVM ) Berbasis Particle Swarm Optimization ( PSO ). Jurnal Bianglala Informatika, 3(2), 1–9.




DOI: http://dx.doi.org/10.30645/senaris.v1i0.83

Refbacks

  • There are currently no refbacks.


&nbsp