Use of the C4.5 Algorithm in Determining Scholarship Recipients

Abstract

The importance of education is increasingly felt by the community. Various attempts were made by parents to continue education for their children. This is in line with the government’s efforts to equalize education. Currently, there are quite a lot of scholarships provided by the government in developing education. One of these scholarships is the Bidik Misi Scholarship. This scholarship is in great demand by prospective students because the period for giving is 4 years and is given every semester. Every year the number of applicants for this scholarship continues to grow. The process of selecting scholarship recipients is getting more complicated due to a large number of candidates for scholarship recipients. The purpose of this research is to develop a system that can assist in selecting prospective scholarship recipients. The method used is Research and Development (RnD) with 4D (Define, Design, Develop, and Disseminate). The system development takes advantage of data mining in classifying the pile of scholarship applicant data using the C4.5 algorithm. The result of the product test shows that the value of the test of vitality is 0.91 which means valid, the practicality test is 0.89 which means that it is practical and the value of the effectiveness test is 0.93 which means that it is effective. These results are shown by the research results obtained from 7 rules with an accuracy rate of 72.5%.

Penerapan Metode Data Mining C4.5 dalam Penentuan Kelayakan Rehabilitas Rumah Warga

“…Selanjutnya buat cabang untuk tiap nilai, bagi kasus dalam cabang, ulangi perhitungan Gain sampai semua data masuk kedalam kelas yang sama. Atribut yang telah dipilih tidak lagi dibutuhkan dalam perhitungan, proses pembentukan pohon keputusan terhenti jika sudah tidak ada lagi atribut yang dipartisi dan semua tuple dalam node N telah memiliki kelas yang sama [15], [16]. Dalam kasus dataset pada penelitian ini terdiri dari 2 kelas keterangan yaitu layak dan tidak layak.…”

Application of the forward selection strategy to the C4.5 Algorithm to improve the classification's accuracy of a breast cancer data set

“…In data mining, classification approaches, such as the C4.5 algorithm, Nave Bayes, Neural Network, and K-Nearest Neighbor, are frequently utilized by academics to solve difficulties. [9][10][11][12] The classification technique is also one of the most extensively researched algorithms. [13][14][15][16] During the past decade, numerous researchers have employed classification approaches to solving breast cancer cases.…”