Penerapan Metode Klasifikasi dan Seleksi Fitur untuk Meprediksi Minat Studi dan Karir Siswa

(Studi Kasus SMK Se-Kabupaten Kudus)

Authors

  • Aditia Candra Kusuma Universitas Stikubank
  • Eka Ardhianto Universitas Stikubank

DOI:

https://doi.org/10.55606/jitek.v5i3.7814

Keywords:

Student interests, further studies, career, Naïve Bayes, Forward Selection

Abstract

Every year, vocational high schools in Kudus Regency produce competitive graduates in the national and international job markets, because vocational high school graduates must be equipped with technical skills and soft skills. However, students face a dilemma in determining the next step in choosing a study interest or career. In addition, several factors influence student interests, one of which is family beckground, so that students who were initially sure will become unsure of their interests. Therefore, the purpose of this study is to classify student interests. The use of classification methods with the naïve bayes algorithm and feature selection with forward selection was chosen in this study. Classification model testing was carried out three times with a comparison of training data and test data (90:10, 80:20, and 70:30), where the results obtained had an average accuracy value of 72.85%, an averagr precision velue of 77.75%, and an average recall value of 86.43%. the classification results are continued with the application of forward selection to find influential attributes, and the results of feature selection show that major attribute, achievement attributes, and mathematics value attributes have an influence on student interest.

References

[1] D. Nofitasary, Y. Rahmawati, and Suprianto, “Klasifikasi Minat Karir Siswa Sekolah Menengah Atas Menggunakan Algoritma C4.5,” Jutisi, vol. 13, pp. 711–724, 2024.

[2] A. Doahir and A. N. Qolbi, “Analisis Potensi Siswa Untuk Kuliah Dengan Classification Menggunakan Metode Decision Tree,” J. POROS Tek., vol. 14, no. 1, 2022.

[3] G. M. Momole, “Perbandingan Naïve Bayes dan Random Forest Dalam Klasifikasi Bahasa Daerah,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 9, no. 2, 2022, doi: 10.35957/jatisi.v9i2.1857.

[4] N. I. P. N. M. F. B. B. M. A. Nazal, “Analisis Perbandingan Metode Feature Selection Backward Method dan Stepwise Method,” J. Stat. Data Sci., 2024.

[5] G. W. N. Wibowo, “PREDIKSI KELANJUTAN STUDI SISWA KE PERGURUAN TINGGI DENGAN NAIVE BAYES,” J. DISPROTEK, vol. 11, no. 1, 2020, doi: 10.34001/jdpt.v11i1.1159.

[6] M. R. Fanani, “Penggabungan Forward Selection untuk Pemilihan Fitur pada Prediksi Bimbingan Konseling Siswa dengan Menggunakan Algoritma Naive Bayes,” Smart Comp Jurnalnya Orang Pint. Komput., vol. 9, no. 2, 2020, doi: 10.30591/smartcomp.v9i2.1924.

[7] Suprapto, “Improvement Naive Bayes Menggunakan Forward Selection, Information Gain dan Gain Ratio untuk Penanganan Independensi Fitur,” J. Sos. dan Teknol., vol. 5 No. 4, 2025.

[8] L. Pebrianti, E. Simamora, U. Manullang, N. Taufiq, and Chairunisah, “PERBANDINGAN METODE ALGORITMA SUPERVISED NAiVE BAYES DAN SUPPORT VECTOR MACHINE (SVM) DALAM KLASIFIKASI PENDERITA STUNTING DI KABUPATEN DELI SERDANG,” Mhs. Tek. Inform., vol. 9 No. 3, 2025.

Downloads

Published

2025-11-29

How to Cite

Aditia Candra Kusuma, & Eka Ardhianto. (2025). Penerapan Metode Klasifikasi dan Seleksi Fitur untuk Meprediksi Minat Studi dan Karir Siswa: (Studi Kasus SMK Se-Kabupaten Kudus). Jurnal Informatika Dan Tekonologi Komputer (JITEK), 5(3), 185–196. https://doi.org/10.55606/jitek.v5i3.7814

Similar Articles

1 2 3 > >> 

You may also start an advanced similarity search for this article.