Penerapan Metode Decision Tree Dalam Menentukan Kelulusan Mahasiswa
-
Fitria Rahmadayanti
*
Sekolah Tinggi Teknologi Pagaralam, Pagar Alam,
Indonesia
- Inda Anggraini Sekolah Tinggi Teknologi Pagaralam, Pagar Alam, Indonesia (*) Corresponding Author
Abstract
The purpose of this study is to produce a prediction system for determining the determination of student graduation on time with the Decision Tree method at Pagaralam High School of Technology. If many students graduate not on time or exceed the specified limit will result in the accumulation of students in large numbers due to the imbalance of the number of students entering and exiting each graduation period so that it can cause the academic process does not run optimally. Decision Tree is a classification algorithm that can predict large amounts of data. The development method used is the Rapid Application Develoment (RAD) method consisting of Requirement Planning (Requirements Planning), Workshop Design, Implementation (Implementation). This research can help the Pagaralam High School of Technology in seeing whether students will graduate on time or not
Downloads
References
R. Rosnelly et al., “ANALISIS METODE DECISION TREE DALAM,” pp. 131–140.
M. Ridwan, “Sistem Rekomendasi Proses Kelulusan Mahasiswaberbasis Algoritma Klasifikasi C4.5,” J. Ilm. Inform., vol. 2, no. 1, pp. 105–111, 2017, doi: 10.35316/jimi.v2i1.460.
R. H. Kusumodestoni and S. Sarwido, “Komparasi Model Support Vector Machines (Svm) Dan Neural Network Untuk Mengetahui Tingkat Akurasi Prediksi Tertinggi Harga Saham,” J. Inform. Upgris, vol. 3, no. 1, 2017, doi: 10.26877/jiu.v3i1.1536.
N. Y. Septian, “Data Mining Menggunakan Algoritma Naïve Bayes Untuk Klasifikasi Kelulusan Mahasiswa Universitas Dian Nuswantoro,” J. Semant. 2013, pp. 1–11, 2009.
J. Fadlil and W. F. Mahmudy, “Pembuatan Sistem Rekomendasi Menggunakan Decision Tree dan Clustering,” Kursor, vol. 3, No.1, no. 1, pp. 1–10, 2007.
endang supriyadi, “Metode SVM Berbasis PSO untuk Meningkatkan Prediksi Ketepatan Waktu Kelulusan Mahasiswa,” J. Sist. Inf., vol. 6, no. 2, p. 335171, 2017, doi: 10.31227/osf.io/4pyrt.
F. Dwi Meliani Achmad, Budanis, Slamat, “Klasifikasi Data Karyawan Untuk Menentukan Jadwal Kerja Menggunakan Metode Decision Tree,” J. IPTEK, vol. 16, no. 1, pp. 18–23, 2012, [Online]. Available: http://jurnal.itats.ac.id/wp-content/uploads/2013/06/3.-BUDANIS-FINAL-hal-17-23.pdf.
R. T. Wulandari, “Pengertian Data Mining,” Data Min., vol. 7, no. 3, pp. 3–9, 2010.
K. Pustaka, “Penerapan Algoritma Decision Tree Id3 Untuk Prediksi Kelulusan Mahasiswa Jenjang Pendidikan D3 Di Fakultas Teknik Universitas Pandanaran,” Neo Tek., vol. 5, no. 2, pp. 2–6, 2019, doi: 10.37760/neoteknika.v5i2.1391.
A. Romadhona, Suprapedi, and H. Himawan, “Prediksi Kelulusan Mahasiswa Tepat Waktu Berdasarkan Usia, Jenis Kelamin, Dan Indeks Prestasi Menggunakan Algoritma Decision Tree,” J. Teknol. Inf., vol. 13, pp. 69–83, 2017.
I. P. Astuti, “Prediksi Ketepatan Waktu Kelulusan Dengan Algoritma Data Mining C4.5,” Fountain Informatics J., vol. 2, no. 2, p. 5, 2017, doi: 10.21111/fij.v2i2.1067.
A. Rohman and A. Rufiyanto, “Komparasi Model Decision Tree Untuk Prediksi Kelulusan Mahasiswa Di Universitas Pandanaran,” Neo Tek., vol. 6, no. 1, pp. 8–12, 2020, doi: 10.37760/neoteknika.v6i1.1427.
M. A. R. Sikumbang, R. Habibi, and S. F. Pane, “Sistem Informasi Absensi Pegawai Menggunakan Metode RAD dan Metode LBS Pada Koordinat Absensi,” J. Media Inform. Budidarma, vol. 4, no. 1, p. 59, 2020, doi: 10.30865/mib.v4i1.1445.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Penerapan Metode Decision Tree Dalam Menentukan Kelulusan Mahasiswa
Pages: 441-445
Copyright (c) 2021 Fitria Rahmadayanti, Inda Anggraini
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
