PREDIKSI KELULUSAN TEPAT WAKTU DENGAN ALGORITMA C4.5 (STUDI KASUS: PROGRAM STUDI TEKNIK INFORMATIKA UMMI)

Hermawanti, Sarah Novia (2019) PREDIKSI KELULUSAN TEPAT WAKTU DENGAN ALGORITMA C4.5 (STUDI KASUS: PROGRAM STUDI TEKNIK INFORMATIKA UMMI). Skripsi thesis, Universitas Muhammadiyah Sukabumi.

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Abstract

The Informatics Engineering Study Program is one of the Study Programs at the University of Muhammadiyah Sukabumi which every year the incoming student quota not all students can graduate on time in accordance with the study period taken so as to result in the accumulation of a number of old students who do not graduate according to the graduation period. PHP is a collection of program codes that are added to HTML which will later be processed in the processor and the results will be displayed in the browser 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 to understand, flexible, and interesting because it can be visualized in the form of images. Based on this research was conducted to create a system using classification techniques that can process large amounts of data to find patterns that occur in student data. Data processing is used to predict classes that are not yet known, namely in this design prediction of student graduation. The classification technique used is decision treewith the application ofC4.5 algorithm. The input used is in the form of attributes from student data including IP (Performance Index) per semester from semester 1 to 7, and BTQ grades in semester 6. The student data is training sample data used in the preparation of decision trees. This test uses training data of students who have graduated from 2015 to 2018. This knowledge can be utilized by the UMMI Informatics Engineering Study Program as a preventive measure to avoid decreasing student graduation each year.

Item Type: Thesis (Skripsi)
Uncontrolled Keywords: C4.5 Algorithm, Decision Tree, PHP, Timely Graduation Prediction.
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains dan Teknologi > Teknik Informatika
Depositing User: Perpus ID UMMI
Date Deposited: 19 Dec 2019 06:49
Last Modified: 19 Dec 2019 06:49
URI: http://eprints.ummi.ac.id/id/eprint/1180

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