KLASIFIKASI FAKTOR PENYEBAB RENDAHNYA MINAT MAHASISWA DALAM MENULIS ARTIKEL ILMIAH

Authors

  • Frskila Parhusip STIKOM Tunas Bangsa Pematangsiantar
  • Agus Perdana Windarto STIKOM Tunas Bangsa Pematangsiantar
  • Irfan Sudahri Damanik STIKOM Tunas Bangsa Pematangsiantar
  • Eka Irawan STIKOM Tunas Bangsa Pematangsiantar
  • Ilham Syahputra Saragih STIKOM Tunas Bangsa Pematangsiantar

DOI:

https://doi.org/10.31598/jurnalresistor.v4i2.700

Keywords:

Scientific Articles, Colleges, Students, Data Mining, C4.5 Algorithm

Abstract

Scientific articles are scientific articles in the form of reviews and research to be published in reputable scientific articles. This is one of the main things that becomes a reference for students in higher education during their studies and at the end of their studies. then the problem that must be faced is how to classify the factor of low student interest and being able to increase student interest in writing scientific articles. The factors of low student interest in writing scientific articles are the level of understanding, motivation, difficulty level, time, and infrastructure. The data used comes from questionnaire data from students of the 2016 batch of information systems study program. It has been obtained that the factor classification of the low interest of students in writing scientific articles is the factor that has top priority on the factor of low student interest is the infrastructure. The results showed that the C4.5 Decision Tree Algorithm was accurate for classifying the factors of low student interest in writing scientific articles with an accuracy rate of 100%.

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References

N. Rofiqo, A. P. Windarto, and A. Wanto, “Penerapan Metode VIKOR Pada Faktor Penyebab Rendahnya Minat Mahasiswa Dalam Menulis Artikel Ilmiah,” Semin. Nas. Sains Teknol. Informasi(SENSASI), no. Mcdm, pp. 228–237, 2018.

H. Sulastri and A. I. Gufroni, “Penerapan Data Mining Dalam Pengelompokan Penderita Thalassaemia,” J. Teknol. dan Sist. Inf., vol. 3, no. 2, p. 299, 2017.

P. Algoritma and C. Untuk, “Penerapan algoritma c4.5 untuk prediksi penggunaan jenis kontrasepsi berbasis web,” vol. 04, no. 02, pp. 174–187, 2017.

N. W. Wardani et al., “PREDIKSI CUSTOMER CHURN DENGAN ALGORITMA DECISION TREE C4 . 5,” vol. 1, no. 1, pp. 16–24, 2018.

A. H. Nasrullah, “PENERAPAN METODE C4.5 UNTUK KLASIFIKASI MAHASISWA BERPOTENSI DROP OUT,” ILKOM, vol. 10, no. 2, pp. 244–250, 2018.

A. P. Windarto, P. Studi, S. Informasi, and D. Mining, “Penerapan Data Mining Pada Ekspor Buah-Buahan Menurut Negara Tujuan Menggunakan K-Means Clustering,” vol. 16, no. 4, pp. 348–357, 2017.

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Published

2021-10-28

How to Cite

Parhusip, F., Windarto, A. P., Damanik, I. S., Irawan, E., & Saragih, I. S. (2021). KLASIFIKASI FAKTOR PENYEBAB RENDAHNYA MINAT MAHASISWA DALAM MENULIS ARTIKEL ILMIAH. Jurnal RESISTOR (Rekayasa Sistem Komputer), 4(2), 134–141. https://doi.org/10.31598/jurnalresistor.v4i2.700

Issue

Vol. 4 No. 2 (2021): Jurnal RESISTOR Edisi Oktober 2021

Section

Articles

License

Copyright (c) 2021 friskila parhusip

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