Penerapan Algoritma C4.5 untuk Seleksi Penerimaan Siswa Baru pada SD Islam Terpadu Permata Bunda Demak Implementation of Decision Tree Algorithm for Selection of New Student Admission on Permata Bunda Integrated Islamic Elementary School

Main Article Content

Linda Monizah Fitriani Andik Setyono

Abstract

The new admission process of selection is a basic rules for determining studying and learning in schools. This process requires precision so that the results are accurate and precise. The selection process for new students are divided into two types of screening, assessment tests and interviews. The purpose of this study is to assist schools in selecting prospective students so that they can be a decision support for new students. Thus, the need for data mining approach to generate information that can support decision-making for new admissions. The algorithm used is a C4.5 decision tree. C4.5 algorithms can support decision making new admissions through the rules generated. The testing process with RapidMiner yield 90.50% accuracy. Based on these tests, the researchers reprocess into the application form to help the school. So, do the questionnaire to the school to investigate the role of applications in the form of 10 questions by 20 teachers and an index of 81.5%. Thus, schools are satisfied with the application and can help the selection process by the school

Downloads

Download data is not yet available.

Article Details

How to Cite
[1]
L. Fitriani and A. Setyono, “Penerapan Algoritma C4.5 untuk Seleksi Penerimaan Siswa Baru pada SD Islam Terpadu Permata Bunda Demak Implementation of Decision Tree Algorithm for Selection of New Student Admission on Permata Bunda Integrated Islamic Elementary School”, CCIT (Creative Communication and Innovative Technology) Journal, vol. 11, no. 2, pp. 158-170, Aug. 2018.
Section
Articles

References

[1] Suharsimi Arikunto, Manajemen Pendidikan.: Aditiya Media Bekerja Sama Dengan FIP, 2002.
[2] Oemar Hamalik, Pendekatan Baru Strategi Belajar Mengajar Berdasarkan CBSA. Bandung: Sinar Baru, 2001.
[3] Syarif Ismet, Manajemen Pendidikan di Sekolah.: CV inti buku utama, 1976. Dikutip oleh Suryosubroto. 2004.
[4] Fitroh Rizqi Muwaddah and Anggi Ricardus, "Penentuan Penerimaan Siswa Baru menggunakan decision tree," p. 7, 2015.
[5] Castaka Agus Sugianto, "Penerapan Teknik Data Mining Untuk Menentukan Hasil Seleksi Masuk Sman 1 Gibeber Untuk Siswa Baru Menggunakan Decision Tree" TEDC, vol. 9, p. 5, januari 2015.
[6] Melda Kusmawathy, "Perancangan Dan Implementasi Data Mining Dalam Proses Penerimaan Siswa Baru Dengan Metode Quantitative Association Rule," Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru, 2011.
[7] Daniel T Larose, Discovering Knowledge in Data : An Introduction to Data Mining.: Wiley Interscience, 2005.
[8] Mochamad Rizki Ilham S, "Implementasi Data Mining Menggunakan Algoritma C4.5 Untuk Prediksi Kepuasan Pelanggan Taksi Kosti," Skripsi Teknik Informatika Universitas Dian Nuswantoro, Semarang, 2016.
[9] G. L. Agrawal1 and H. Gupta, “Optimization of C4.5 Decision Tree Algorithm for Data Mining Application”, International Journal of Emerging Technology and Advanced Engineering, Volume 3, Issue 3, March 2013
[10] R. Sudrajat et. al., Analysis of data mining classification by comparison of C4.5 and ID algorithms”, IOP Conference Series: Materials Science and Engineering, 2017
[11] L. A. Bădulescu, “Data mining classification experiments with decision trees over the forest covertype database”, 2017 21st International Conference on System Theory, Control and Computing (ICSTCC), IEEE, Romania, 2017.
[12] B. Hssina, et. al., “A comparative study of decision tree ID3 and C4.5”, International Journal of Advanced Computer Science and Applications, Special Issue on Advances in Vehicular Ad Hoc Networking and Applications, 2013.
[13] W. Dai and W. Ji, “A MapReduce Implementation of C4.5 Decision Tree Algorithm” International Journal of Database Theory and Application, Vol. 7, No. 1, 2014