C4.5 Algorithm Application for Prediction of Self Candidate New Students in Higher Education

Authors

  • Erlan Darmawan Universitas Kuningan Asia E University, Indonesia

DOI:

https://doi.org/10.15575/join.v3i1.171

Keywords:

C4.5 Algorithm, Retirement New Student Candidate, Prediction, Waterfall

Abstract

Data mining has background with the condition of an abundance of data (the overload data) and the explosion information faced by companies, institutions or organizations that are stored for many years. This situation is also faced in several universities that stores various kinds of data, especially new admissions database. But the abundant data has not been widely used in digging the information or knowledge that can help university management in making strategic plans. Every year there are new students who retire that do not register,therefore, it takes an application that can process a lot of data to find out the possible retirement for new students. To find out the prediction retirement prospective students, this paper uses C.45 algorithm. The method can change the a very large fact into a decision tree that represents the rule. The result of this research is that the application can classify the new students in tree structure in order that it can produce a rule. This application is able to predict the possibility of the retirement of new student. With this application, it  is expected that the possibility of a prospective student will retire from college can be known at an early stage, so the management can make a decision easily. Development of this application built uses PHP as the interface application system and MySql in database processing. System development methodology used is the waterfall model

Author Biography

Erlan Darmawan, Universitas Kuningan Asia E University

kepala bagian penelitian universitas kuningan

References

U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, Advances in Knowledge Discovery and Data Mining, vol. 3918. 1996.

E. Darmawan, Sistem Penunjang Keputusan Penerimaan Beasiswa Menggunakan Fuzzy Multiple Attribute Decision Making(FMADM). Nuansa Informatika, 2013.

E. Endarmoko, Tesaurus Bahasa Indonesia. Gramedia, 2006.

Pusat Bahasa Departemen Pendidikan Nasional, Kamus Besar Bahasa Indonesia (Fourth Edition). 2008.

Kusrini and E. T. Luthfi, Algoritma Data Mining. Yogyakarta: Andi, 2009.

D. T. Larose, Discovering knowledge in data: an introduction to data mining, vol. 28, no. 1. 2005.

I. Pramudiono, “Apa Itu Data Mining?,†2006. [Online]. Available: https://datamining.japati.net/cgibin/indodm.cgi?bacaarsip&1155 52767&artikel.

H. . Kusrini, Hartati.S, Wardoyo.R, “Perbandingan metode nearest neighbor dan algoritma c4.5 untuk menganalisis kemungkinan pengunduran diri calon mahasiswa di stmik amikom yogyakarta,†J. Dasi, vol. 10(1), no. 1, pp. 1–132, 2009.

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Published

2018-06-30

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