Penerapan Data Mining Pada Penerimaan Dosen Tetap Menggunakan Metode Naive Bayes Classifier dan C4.5

 (*)Muhammad Sadikin Mail (Universitas Potensi Utama, Medan, Indonesia)
 Rika Rosnelly (Universitas Potensi Utama, Medan, Indonesia)
 Roslina Roslina (Universitas Potensi Utama, Medan, Indonesia)
 Teddy Surya Gunawan (Universitas Potensi Utama, Medan, Indonesia)
 Wanayumini Wanayumini (Universitas Potensi Utama, Medan, Indonesia)

(*) Corresponding Author

Submitted: August 31, 2020; Published: October 20, 2020

DOI: http://dx.doi.org/10.30865/mib.v4i4.2434

Abstract

Recruitment is an important step in creating professional HR (Human Resources). The application of classification methods such as the Naïve Bayes method and C4.5 can be used in the classification of potential lecturers and can be accepted by the campus by calculating the equations for each criterion. The difficulty experienced is the ineffective use of the method to generate the required lecturer acceptance so that it is not in accordance with the applicant's expertise. One of the classification methods applied to data mining is the naïve Bayes method and C4.5. The purpose of this study is to determine the level of accuracy of the two methods used by using the Weka 3.8 tool based on the calculation of Correctly Classified Instance and Incorrectly Classified Instance. The accuracy results obtained with the naïve Bayes method are 83.7838% and the C4.5 method is 91.8919% from 37 training data. So the C4.5 method is a more appropriate method to use than naïve Bayes.

Keywords


Classification, Data Mining, Recruitment, Naïve Bayes, Weka

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References

E. H. M. E. H. A. Sakinah Mat Zin, N. N. Jaafar, Rosfatihah Che Mat, W. Nurfahizul Ifwah W. Alias, “E-recruitment technology: the effective source of recruitment.,” vol. vol 6, p. 84–89., 2016.

Marwansyah, Manajemen sumber daya manusia. KOTA MAKASSAR: Alfabeta, 2016.

A. Amrin, “Perbandingan Metode Neural Network Model Radial Basis Function Dan Multilayer Perceptron Untuk Analisa Risiko Kredit Mobil,” Paradigma, vol. XX, no. 1, pp. 31–38, 2018.

E. Buulolo, Data Mining Untuk Perguruan Tinggi. Deepublish, 2020.

Y. Mardi, “Data Mining : Klasifikasi Menggunakan Algoritma C4.5,” J. Edik Inform., vol. 2, no. 2, pp. 213–219, 2017.

D. Srianto and E. Mulyanto, “Perbandingan K-Nearest Neighbor Dan Naive Bayes,” Techno.COM, vol. 15, no. 3, pp. 241–245, 2016.

S. Yakub, A. Fitri Boy, I. Mariami, W. Stmik, and T. Dharma, “J-SISKO TECH Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Penerapan Data Mining Pengaturan Pola Tata Letak Barang Pada Berkah Swalayan Untuk Strategi Penjualan Menggunakan Algoritma Apriori,” , vol. 69, no. 1, pp. 69–75, 2019.

E. Etriyanti, D. Syamsuar, and N. Kunang, “Implementasi Data Mining Menggunakan Algoritme Naive Bayes Classifier dan C4.5 untuk Memprediksi Kelulusan Mahasiswa,” Telematika, vol. 13, no. 1, pp. 56–67, 2020.

Y. A. Gerhana, I. Fallah, W. B. Zulfikar, D. S. Maylawati, and M. A. Ramdhani, “Comparison of naive Bayes classifier and C4.5 algorithms in predicting student study period,” J. Phys. Conf. Ser., vol. 1280, no. 2, 2019.

E. N. Azizah, U. Pujianto, E. Nugraha, and Darusalam, “Comparative performance between C4.5 and Naive Bayes classifiers in predicting student academic performance in a Virtual Learning Environment,” 2018 4th Int. Conf. Educ. Technol. ICET 2018, no. 1, pp. 18–22, 2018.

yogiek indra Kurniawan, “PERBANDINGAN ALGORITMA NAIVE BAYES DAN C.45 DALAM KLASIFIKASI DATA MINING,” J. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 4, pp. 455–464, 2018.

T. Arifin, “Metode Data Mining Untuk Klasifikasi Data Sel Nukleus Dan Sel Radang Berdasarkan Analisa Tekstur,” Informatika, vol. II, no. 2, pp. 425–433, 2015.

A. Saleh, “Implementasi Metode Klasifikasi Naïve Bayes Dalam Memprediksi Besarnya Penggunaan Listrik Rumah Tangga,” Creat. Inf. Technol. J., vol. 2, no. 3, pp. 207–217, 2015.

W. D. Septiani, “Komparasi Metode Klasifikasi Data Mining Algoritma C4.5 Dan Naive Bayes Untuk Prediksi Penyakit Hepatitis,” J. Pilar Nusa Mandiri, vol. 13, no. 1, pp. 76–84, 2017.

E. Buulolo, N. Silalahi, Fadlina, and R. Rahim, “C4.5 Algorithm To Predict the Impact of the Earthquake,” Int. J. Eng. Res. Technol., vol. 6, no. 2, 2017.

N. Azwanti, “Algoritma C4.5 Untuk Memprediksi Mahasiswa Yang Mengulang Mata Kuliah (Studi Kasus Di Amik Labuhan Batu),” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 9, no. 1, pp. 11–22, 2018.

A. Saleh, “Penerapan Data Mining Dengan Metode Klasifikasi Naive Bayes Untuk Memprediksi Kelulusan Mahasiswa Dalam Mengikuti English Proficiency Test (Studi Kasus : Universitas Potensi Utama),” Konf. Nas. Sist. Informasi, Univ. Klabat,Manado,Indonesia, Vol. 2015, no. February 2015, pp. 1–6, 2015.

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