STUDI PERBANDINGAN DECISION TREE DAN RULE BASED UNTUK PENJADWALAN PEMINJAMAN LABORATORIUM SEKOLAH
DOI:
https://doi.org/10.29407/f27c2a13Abstract
Penelitian ini membandingkan antara algoritma Decision Tree (C4.5) dan metode Rule Based dalam mengatasi masalah penjadwalan peminjaman laboratorium yang dilakukan secara manual di SMP Negeri 1 Rejoso. Sekolah itu hanya memiliki 2 laboratorium sains yang digunakan oleh 6 guru dan 27 kelompok belajar, dengan 9 kelompok per kelas 7, 8, dan 9.Karena itu, jadwal sering bertabrakan hingga terjadi 15 kasus per minggu. Decision tree dilatih menggunakan 100 data historis yang mencakup fitur seperti hari, ruangan, jam pelajaran, rombel, guru, dan status ketersediaan, serta mengaplikasikan rumus entropy dan information gain. Sebaliknya, metode Rule Based diambil dari sistem berbasis web (PHP & MySQL) yang menggunakan aturan seperti memeriksa kekosongan ruang, mendeteksi tumpang tindih jadwal, dan menentukan prioritas kelas. Hasil perbandingan menunjukkan bahwa Decision Tree mencapai akurasi sebesar 92,4%, dengan penurunan bentrok sebesar 86,7% dan peningkatan efisiensi waktu sebesar 45%.Sementara itu, Rule Based mencapai akurasi 94%, dengan keunggulan dalam hal kemudahan dalam memahami dan mengubah aturan. Studi ini menunjukkan bahwa Decision Tree lebih baik dalam menghadapi pola yang rumit, sedangkan Rule Based lebih cocok untuk aturan yang tetap di sekolah. Hasil penelitian memberikan rekomendasi hybrid untuk optimalisasi manajemen laboratorium IPA di sekolah menengah.
Keywords:
pohon keputusan, berbasis aturan, penjadwalan, peminjaman laboratorium, studi perbandingan, entropi.##plugins.themes.default.displayStats.downloads##
References
[1] Q. M. I. K. Wati, H. Fitria, and A. Y. Putra, “Science Laboratory Management in
Learning,” J. Soc. Work Sci. Educ., vol. 5, no. 2, 2024, doi: 10.52690/jswse.v5i2.761.
[2] E. S. P. Giawa, T. Mary, and A. A. Samudra, “Perancangan Sistem Informasi
Penjadwalan Laboratorium Pendidikan Informatika Universitas PGRI Sumatera Barat,”
JURTEII J. Teknol. Inf., vol. 1, no. 2, pp. 1–6, 2022, doi: 10.22202/jurteii.2022.5706.
[3] K. S. Devi, R. A. Pratama, Y. Sa’adati, and ..., “Rancang Bangun Sistem Informasi
Penjadwalan Berbasis Web Pada Laboratorium Kesehatan Universitas Qamarul Huda
Badaruddin,” SainsTech Innov. …, vol. 5, no. November, 2022, [Online]. Available:
http://jkqh.uniqhba.ac.id/index.php/sij/article/view/421
[4] Andhika Rizky Aulia, Eka Dyar Wahyuni, and Reisa Permatasari, “Backend Design and
Development of Thesis Management and Scheduling Application Using Rule-Based
Algorithm in Physics Department UPN ‘Veteran’ Jatim,” J. Teknol. Dan Open Source,
vol. 8, no. 1, pp. 153–163, 2025, doi: 10.36378/jtos.v8i1.4386.
[5] A. Hidayati, A. Argianto, and B. P. Rini, “Inovasi Sistem Penjadwalan Laboratorium
Terpadu melalui Aplikasi M-Room berbasis Google Spreadsheet di Poltekkes Kemenkes
Jakarta I,” J. Pengelolaan Lab. Pendidik., vol. 7, no. 2, pp. 139–150, 2025, doi:
10.14710/jplp.7.2.139-150.
[6] A. Dalimunthe, A. C. Sari, B. Maulana, F. Syahputra, and E. D. Suryanto, “RANCANG
BANGUN SISTEM INFORMASI MANAJEMEN PENGELOLAAN
LABORATORIUM BERBASIS WEB DI SEKOLAH MENENGAH KEJURUAN,” J.
10.24114/jtikp.v10i2.54116.
[7] J. R. Lex, A. Abbas, J. S. Toor, E. B. Khalil, B. Ravi, and C. M. Whyne, “Smart
scheduling of arthroplasty surgery with machine learning and optimisation improves
operating room utilisation,” BMJ Heal. care informatics, vol. 33, no. 1, pp. 1–7, 2026,
doi: 10.1136/bmjhci-2024-101420.
[8] A. Fadlil, D. P. M, M. Ma’ruf, and Furizal, “Machine Learning-Based Early Prediction
of Stunting Risk: A Comparative Study,” Methods Sci. Technol. Stud., vol. 1, no. 1, pp.
24–31, 2025, doi: 10.64539/msts.v1i1.2025.351.
[9] X. Yang, “Construction and Application of Machine Learning Prediction Models for
Library Space Utilization Efficiency,” J. Comb. Math. Comb. Comput., vol. 127b, no.
October 2024, pp. 1801–1813, 2025, doi: 10.61091/jcmcc127b-100.
[10] Ramesh Krishna Mahimalur, “Machine Learning Approaches for Resource Allocation in
Heterogeneous Cloud-Edge Computing,” Int. J. Sci. Res. Comput. Sci. Eng. Inf.
Technol., vol. 11, no. 2, pp. 2739–2748, 2025, doi: 10.32628/cseit25112758.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Copyright on any article is retained by the author(s).
- The author grants the journal, right of first publication with the work simultaneously licensed under a Creative Commons Attribution 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.
- The article and any associated published material is distributed under the Creative Commons Attribution-ShareAlike 4.0 International License
