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Implementasi Algoritma C4.5 Untuk Prediksi Kelulusan Tepat Waktu

(Studi Kasus: Program Studi Teknik Informatika)
Authors: Sarah Novia Hermawanti; Asriyanik Asriyanik; Asril Adi Sunarto;

Implementasi Algoritma C4.5 Untuk Prediksi Kelulusan Tepat Waktu

Abstract

The Informatics Engineering Study Program is one of the Study Programs at the University ofMuhammadiyah Sukabumi which every year the incoming student quota not all students can graduate ontime in accordance with the study period taken so as to result in the accumulation of a number of old studentswho do not graduate according to the graduation period. PHP is a collection of program codes that areadded to HTML which will later be processed in the processor and the results will be displayed in thebrowser as HTML pages. C4.5 algorithm is the result of the development of the ID3 (Iterative Dichotomiser)algorithm which was developed by Quinlan. This algorithm is used to build a decision tree that is easy tounderstand, flexible, and interesting because it can be visualized in the form of images. Based on thisresearch was conducted to create a system using classification techniques that can process large amounts ofdata to find patterns that occur in student data. Data processing is used to predict classes that are not yetknown, namely in this design prediction of student graduation. The classification technique used is decisiontree with the application of C4.5 algorithm. The input used is in the form of attributes from student dataincluding IP (Performance Index) per semester from semester 1 to 7, and BTQ grades in semester 6. Thestudent data is training sample data used in the preparation of decision trees. This test uses training data ofstudents who have graduated from 2015 to 2018. This knowledge can be utilized by the UMMI InformaticsEngineering Study Program as a preventive measure to avoid decreasing student graduation each year

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
hybrid