Identifikasi Faktor Tidak Diterimanya Siswa Mau Amanatul Ummah Pada Perguruan Tinggi Melalui Jalur SPAN-PTKIN Menggunakan Metode Klasifikasi Algoritma C4.5

Zahria, Ismi (2019) Identifikasi Faktor Tidak Diterimanya Siswa Mau Amanatul Ummah Pada Perguruan Tinggi Melalui Jalur SPAN-PTKIN Menggunakan Metode Klasifikasi Algoritma C4.5. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Madrasah Aliyah Unggulan Amanatul Ummah merupakan salah satu sekolah jenjang SLTA yang bertempat di Pacet, Mojokerto. Seperti layaknya sekolah tingkat SLTA pada umumnya, MAU Amanatul Ummah berusaha untuk mengarahkan peserta didik untuk mendapatkan kursi di jurusan dan perguruan tinggi ketika menyelesaikan masa SLTA.
Penelitian ini bertujuan untuk mengetahui atribut yang mempengaruhi kegagalan alumni MAU Amanatul Ummah ketika memasuki jenjang perkuliahan melalui jalur SPAN-PTKIN, dan mengusulkan perbaikan untuk meningkatkan jumlah peserta didik yang diterima pada perguruan tinggi.
Penelitian ini menggunakan metode machine-learninng sebagai referensi untuk pembuatan pola diterimanya siswa MAU Amanatul Ummah di perguruan tinggi melalui jalur SPAN-PTKIN dengan model klasifikasi dari data yang didapatkan. Algoritma C4.5 dapat digunakan pada penelitian dengan model data seperti ini. Hal ini ditunjukkan dengan nilai akurasi yang cukup tinggi yakni 64.15% dan nilai presisi di atas 0.5 yakni 0.694 untuk label Tidak Diterima dan 0.529 untuk label Diterima.
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MAU Amanatul Ummah is one of senior high school level located in Mojokerto,
Indonesia. Like any other high school level in general, MAU Amanatul Ummah is
trying to direct its students to get seats in majors and universities when
completing high school.
This study aims to find out the attributes that affect of MAU Amanatul Ummah
alumni when entering the university level through the SPAN-PTKIN pathway and
propose improvements to increase the number of students accepted to universities
in the next year.
This study uses the machine-learning method as a reference for making patterns of
MAU Amanatul Ummah students in universities through the SPAN-PTKIN
pathway with a classification model of the data obtained. The C4.5 algorithm can
be used in research with data models like this.
In this study, several data mining processes were carried out. Starting with the
annual group selection, data obtained from 2018 Type 2 graduate has the highest
score. Followed by variations in the attributes used, the result is better when all
grades of the report are used from semester 1-5. Finally, the test uses all attributes
in the data group of 2018 Type 2 Graduates.
The result of this research was good as indicated by a fairly high accuracy value
of 64.15% and a precision value above 0.5, which is 0.694 for labels Not
Accepted and 0.529 for labels Accepted. Also, the error value for the data is not
too far from the model.

Item Type: Thesis (Masters)
Additional Information: RTMT 005.1 Zah i-1 2019
Uncontrolled Keywords: Educational Data Mining, Klasifikasi, Algoritma C4.5
Subjects: L Education > L Education (General)
Q Science > QA Mathematics > QA402.5 Genetic algorithms.
Q Science > QA Mathematics > QA76.9.D343 Data mining. Querying (Computer science)
T Technology > T Technology (General)
Divisions: Faculty of Creative Design and Digital Business (CREABIZ) > Technology Management > 61101-(S2) Master Thesis
Depositing User: Zahria Ismi
Date Deposited: 31 Oct 2021 14:17
Last Modified: 31 Oct 2021 15:07
URI: http://repository.its.ac.id/id/eprint/61512

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