The Implementation of C4.5 Algorithm for Determining the Department of Vocational High School

Authors

  • Mirza Sutrisno Universitas Muhammadiyah Jakarta
  • Jefri Kusuma Rambe Universitas Budi Luhur
  • Asruddin Asruddin Universitas Bung Karno
  • Ade Davy Wiranata Universitas Muhammadiyah Prof. Dr. HAMKA
(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v5i2.211

Keywords:

C4.5 Algorithm, Department Selection, Recommendation System, Vocational School

Abstract

The selection of departments in vocational high schools (SMK) is a must for students to determine the concentration of student learning interest for three years in a school. The lack of student knowledge and outreach about this department caused many students to choose their majors by the most choices and following other students. This problem can cause some difficulties for the students to participate in learning, and most fail. Students must select their major based on their interests, abilities, and talents because every student has different abilities and talents. The C4.5 algorithm can provide convenience in grouping students based on majors. Using the decision tree method with attributes such as grades in mathematics, English, interests, and talents, the system can recommend majors based on students' interest levels. The results of this study are the determination of the departments with the accuracy of the calculation using the confusion matrix method with a 98,55% accuracy rate and 100% recall rate value.

Downloads

Download data is not yet available.

References

Azwanti, N. (2018). Algoritma C4.5 Untuk Memprediksi Mahasiswa Yang Mengulang Mata Kuliah (Studi Kasus Di Amik Labuhan Batu). Simetris: Jurnal Teknik Mesin, Elektro Dan Ilmu Komputer, 9(1), 11–22. https://doi.org/10.24176/simet.v9i1.1627

Baktiar, A. (2022). Decission Tree Sebagai Metode Penentuan Penjurusan Perguruan Tinggi Berdasarkan Minat Dan Bakat Melalui Data Raport Dengan Uji Algoritma C4 . 5. Jurnal Pilar Teknologi, 7(1), 40–45. https://doi.org/10.33319/piltek.v7i1.110

Darmawan, E. (2018). C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education. Jurnal Online Informatika, 3(1), 22. https://doi.org/10.15575/join.v3i1.171

Khairina, D. M., Ramadhani, F., Maharani, S., & Hatta, H. R. (2015). Department Recommendations for Prospective Students Vocational High School of Information Technology with Naïve Bayes Method. 2nd International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE), 92–96. https://doi.org/10.1109/ICITACEE.2015.7437777

Kurniasari, R., & Fatmawati, A. (2019). Penerapan Algoritma C4.5 Untuk Penjurusan Siswa Sekolah Menengah Atas. Jurnal Ilmiah Komputer Dan Informatika (KOMPUTA), 8(1), 19–27. https://doi.org/10.34010/KOMPUTA.V8I1.3045

Larose, D. T. (2005). Discovering Knowledge in Data: An Introduction to Data Mining. In Discovering Knowledge in Data: An Introduction to Data Mining (2nd ed., pp. 1–222). John Willey & Sons Inc. https://doi.org/10.1002/0471687545

Luvia, Y. S., Windarto, A. P., Solikhun, S., & Hartama, D. (2017). Penerapan Algoritma C4.5 Untuk Klasifikasi Predikat Keberhasilan Mahasiswa Di AMIK Tunas Bangsa. Jurasik (Jurnal Riset Sistem Informasi Dan Teknik Informatika), 1(1), 75–79. https://doi.org/10.30645/jurasik.v1i1.12

Mulyana, S., Hartati, S., Wardoyo, R., & Winarko, E. (2015). Case-Based Reasoning for Selecting Study Program in Senior High School. International Journal of Advanced Computer Science and Applications, 6(4), 136–140. https://doi.org/10.14569/ijacsa.2015.060418

Normawati, D., & Prayogi, S. A. (2021). Implementasi Naïve Bayes Classifier Dan Confusion Matrix Pada Analisis Sentimen Berbasis Teks Pada Twitter. Jurnal Sains Komputer & Informatika (J-SAKTI, 5(2), 697–711. http://ejurnal.tunasbangsa.ac.id/index.php/jsakti/article/view/369

Prabowo, I. M., & Subiyanto, S. (2017). Sistem Rekomendasi Penjurusan Sekolah Menengah Kejuruan Dengan Algoritma C4.5. Jurnal Kependidikan, 1(1), 139–149. https://doi.org/10.21831/jk.v1i1.8964

Puspitasari, C. (2020). Implementation of C4.5 Method To Determine the Factor of Being Late for Coming To School. Jurnal Riset Informatika, 2(3), 115–120. https://doi.org/10.34288/jri.v2i3.132

Soufitri, F., Purwawijaya, E., Hasibuan, E. H., & Singarimbun, R. N. (2021). Testing C4.5 Algorithm Using RapidMiner Applications in Determining Customer Satisfaction Levels. Jurnal INFOKUM, 9(2), 510–517. https://infor.seaninstitute.org/index.php/infokum/article/view/198

Sutrisno, M., & Budiyanto, U. (2019). Intelligent System for Recommending Study Level in English Language Course Using CBR Method. International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 153–158. https://doi.org/10.23919/EECSI48112.2019.8977047

Swastina, L. (2018). Penerapan Algoritma C4 . 5 Untuk Penentuan Jurusan Mahasiswa. Gema Aktualita, 2(1), 93–98. https://doi.org/10.24252/insypro.v6i2.7912

Turban, E., E. Aronson, J., & Liang, T.-P. (2007). Decision Support Systems and Business Intelligence. Decision Support and Business Intelligence Systems, 7/E, 1–35. https://doi.org/10.1017/CBO9781107415324.004

Downloads

Published

2023-03-25

How to Cite

Sutrisno, M., Rambe, J. K., Asruddin, A., & Wiranata, A. D. (2023). The Implementation of C4.5 Algorithm for Determining the Department of Vocational High School. Jurnal Riset Informatika, 5(2), 211–218. https://doi.org/10.34288/jri.v5i2.211

Issue

Section

Articles