Implementasi Algoritma Rough Set Untuk Memprediksi Jumlah Pendaftar Siswa Baru Pada SMK Swasta Sinar Harapan

Authors

  • Sinta Novianti STMIK PELITA NUSANTARA MEDAN
  • Paska Marto Hasugian STMIK Pelita Nusantara Medan

DOI:

https://doi.org/10.54367/jtiust.v6i2.1433

Keywords:

Data Mining, Prediction, Rough Set

Abstract

ABSTRACT Where the number of new student registrants at the Sinar Harapan Private Vocational School is unstable every year and the school has difficulty predicting how many new student registrants will be in the coming year and preparing extracurricular activities such as English/computer training or the best facilities for new students such as chairs, tables, classrooms and so on, as well as the competitiveness of private schools in the district. banyan. So we need a system that can dig up data and help predict the number of new student registrants, using data mining techniques, namely the Rough Set Algorithm which aims to get a short rule estimate from a table, in this study using student registration data in 2018, 2019, 2020. By applying data mining with the rough set algorithm and carrying out the rough set stages, it can produce decisions in the form of generating rules (knowledge), and the results of the calculation analysis are 152 students to predict the number of students in the coming year.

Author Biographies

Sinta Novianti, STMIK PELITA NUSANTARA MEDAN

ABSTRACT Where the number of new student registrants at the Sinar Harapan Private Vocational School is unstable every year and the school has difficulty predicting how many new student registrants will be in the coming year and preparing extracurricular activities such as English/computer training or the best facilities for new students such as chairs, tables, classrooms and so on, as well as the competitiveness of private schools in the district. banyan. So we need a system that can dig up data and help predict the number of new student registrants, using data mining techniques, namely the Rough Set Algorithm which aims to get a short rule estimate from a table, in this study using student registration data in 2018, 2019, 2020. By applying data mining with the rough set algorithm and carrying out the rough set stages, it can produce decisions in the form of generating rules (knowledge), and the results of the calculation analysis are 152 students to predict the number of students in the coming year.

Paska Marto Hasugian, STMIK Pelita Nusantara Medan

ABSTRACT Where the number of new student registrants at the Sinar Harapan Private Vocational School is unstable every year and the school has difficulty predicting how many new student registrants will be in the coming year and preparing extracurricular activities such as English/computer training or the best facilities for new students such as chairs, tables, classrooms and so on, as well as the competitiveness of private schools in the district. banyan. So we need a system that can dig up data and help predict the number of new student registrants, using data mining techniques, namely the Rough Set Algorithm which aims to get a short rule estimate from a table, in this study using student registration data in 2018, 2019, 2020. By applying data mining with the rough set algorithm and carrying out the rough set stages, it can produce decisions in the form of generating rules (knowledge), and the results of the calculation analysis are 152 students to predict the number of students in the coming year.

References

A. Z. Hasibuan, G. Ginting, and K. Tampubolon, “Prediksi Jumlah Jamaah Pendaftar Umroh dan Haji Plus dengan Algoritma Rough Set (Studi Kasus: PT Annajwa Islamic Tour & Travel),†Inf. dan Teknol. Ilm., vol. 13, pp. 187–191, 2018.

A. Putra, Z. A. Matondang, N. Sitompul, I. Pendahuluan, and A. Prediksi, “Implementasi Algoritma Rough Set Dalam Memprediksi Kecerdasan Anak,†J. Pelita Inform., vol. 7, no. 2, pp. 149–156, 2018.

U. Indriani, “Penerapan Metode Rough Set Dalam Menentukan,†vol. 2, no. 1, pp. 85–92, 2018.

D. Nofriansyah and G. W. Nurcahyo, “Algoritma Data Mining Dan Pengujian,†Algoritma Data Mining dan Pengujian. 2019.

S. Sulaiman, N. A. A. Rahim, and A. Pranolo, “Generated rules for AIDS and e-learning classifier using rough set approach,†Int. J. Adv. Intell. Informatics, vol. 2, no. 2, pp. 103–122, 2016, doi: 10.26555/ijain.v2i2.74.

S. Kasus, P. Sumut, R. Tasya, E. Buulolo, and P. G. M, “Menggunakan Metode Rough Set,†vol. 13, pp. 157–161, 2018.

Arhami, M., & Nasir, M. (2020). Data Mining Algoritma dan Implementasi. Yogyakarta: Andi

Hermawati, F. J. (2018). Data Mining. Yogyakarta: C.V Andi Offset

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Published

2021-11-13

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