BAEDHAWI, AHMAD (2024) PENERAPAN ALGORITMA DECISION TREE C4.5 UNTUK PREDIKSI KENAIKAN KELAS SISWA MI AL-HIDAYAH KEMBANGAN. S1 thesis, Universitas Mercu Buana Jakarta.
|
Text (HAL COVER)
01 COVER.pdf Download (351kB) | Preview |
|
|
Text (ABSTRAK)
02 ABSTRAK.pdf Download (26kB) | Preview |
|
![[img]](https://repository.mercubuana.ac.id/style/images/fileicons/text.png) |
Text (BAB I)
03 BAB 1.pdf Restricted to Registered users only Download (105kB) |
|
|
Text (BAB II)
04 BAB 2.pdf Restricted to Registered users only Download (139kB) |
|
|
Text (BAB III)
05 BAB 3.pdf Restricted to Registered users only Download (146kB) |
|
|
Text (BAB IV)
06 BAB 4.pdf Restricted to Registered users only Download (238kB) |
|
|
Text (BAB V)
07 BAB 5.pdf Restricted to Registered users only Download (33kB) |
|
|
Text (DAFTAR PUSTAKA)
08 DAFTAR PUSTAKA.pdf Restricted to Registered users only Download (126kB) |
|
|
Text (LAMPIRAN)
09 LAMPIRAN.pdf Restricted to Registered users only Download (213kB) |
Abstract
In this research, the Decision Tree C4.5 algorithm is used as a prediction model for student grade advancement at MI Al-Hidayah Kembangan. The analysis uses student academic data, such as end-of-year assessment test scores. For the process of preparing the dataset, the data collection process is carried out, and data preprocessing is carried out to build a prediction model for the C4.5 Decision Tree algorithm. Metrics such as accuracy, precision, and recall are used to assess the model with the hope that the results of this research will provide insight into the factors that influence student grade advancement. On the other hand, it is hoped that the application of the Decision Tree C4.5 algorithm can become the basis for decision making in the education sector. This study explains how data mining technology can help decision making and management of academic data in elementary schools. Keywords: data mining, C4.5 algorithm, class advancement, prediction, students. Dalam penelitian ini, algoritma Decision Tree C4.5 digunakan sebagai model prediksi kenaikan kelas siswa di MI Al-Hidayah Kembangan. Analisis menggunakan data akademik siswa, seperti nilai ujian penilaian akhir tahun. Untuk prosesnya mempersiapkan dataset, dilakukan proses pengumpulan data, dan preprocessing data dilakukan untuk membangun model prediksi algoritma decision Tree C4.5. Metrik seperti akurasi, presisi, dan recall digunakan untuk menilai model yang diharapkan bahwa hasil penelitian ini akan memberikan wawasan tentang faktor yang mempengaruhi kenaikan kelas siswa. Di sisi lain, penerapan algoritma Decision Tree C4.5 diharapkan dapat menjadi dasar untuk pengambilan keputusan di bidang pendidikan. Studi ini menjelaskan bagaimana teknologi data mining dapat membantu pengambilan keputusan dan pengelolaan data akademik di sekolah dasar. Kata kunci: data mining, algoritma C4.5, kenaikan kelas, prediksi, siswa
| Item Type: | Thesis (S1) |
|---|---|
| Call Number CD: | FIK/INFO. 24 124 |
| Call Number: | SIK/15/24/088 |
| NIM/NIDN Creators: | 41520010001 |
| Uncontrolled Keywords: | data mining, algoritma C4.5, kenaikan kelas, prediksi, siswa |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 500 Natural Science and Mathematics/Ilmu-ilmu Alam dan Matematika > 510 Mathematics/Matematika > 518 Numerical Analysis/Analisis Numerik, Analisa Numerik > 518.1 Algorithms/Algoritma |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | khalimah |
| Date Deposited: | 06 Aug 2024 04:34 |
| Last Modified: | 06 Aug 2024 04:34 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/90030 |
Actions (login required)
 |
View Item |
