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Komparasi Algoritma Data Mining Untuk Akurasi Penentuan Beasiswa Kurang Mampu IAIN Syekh Nurjati Cirebon

Year: 2016

Type: article

Abstract: : The scholarships reserved for students who are economically disadvantaged to pay the cost of study in college. The number of criteria used for the determination of scholarships made it difficult to make a decision on granting a scholarship. Besides the time it takes too long. The purpose of this study is the classification of students are not able to Decision Tree, k-NN, NN, which uses the algorithm C4.5. Classification results are evaluated and validated using the area under the curve (AUC) of the ROC curve. Given this comparison can facilitate and accelerate decision-making to provide scholarships for students can not afford. Keywords: classification, scholarship, k-NN, neural network, decision tree, random forest, random tree, data mining.

Source: ITEJ (Information Technology Engineering Journals)

DOI: 10.24235/itej.v1i2.1196

Author: Arif Maulana

Institution: Universitas Dian Nuswantoro

Language: Indonesian

Topic: Data Mining and Machine Learning Applications

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Reduced inequalities

Open Access status: diamond

OpenAlex ID: W2581386863

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