Model Prediksi Kinerja Siswa Berdasarkan Data Log LMS Menggunakan Ensemble Machine Learning

Authors

  • Mifta Ardianti Magister Sistem Informasi, Universitas Diponegoro, Semarang, Indonesia
  • Oky Dwi Nurhayati Magister Sistem Informasi, Universitas Diponegoro, Semarang, Indonesia
  • Budi Warsito Magister Sistem Informasi, Universitas Diponegoro, Semarang, Indonesia

DOI:

https://doi.org/10.23887/jstundiksha.v12i3.59816

Keywords:

Model prediksi, bagging, boosting, voting

Abstract

Institusi pendidikan saat ini menerapkan Learning Management System (LMS) sebagai sarana pembelajaran online. LMS dapat merekam sejumlah besar data perilaku siswa pada log LMS. Data perilaku ini dapat dikumpulkan dan digunakan untuk memprediksi kinerj belajar siswa. Sehingga, diperlukan analisis yang dapat mengubah sejumlah data yang tersimpan tersebut menjadi sebuah pengetahuan yang dapat meningkatkan kualitas pengajaran pada institusi pendidikan. Pada penelitian ini, mengusulkan model prediksi kinerja belajar siswa menggunakan ensemble machine learning berdasarkan ekstraksi ciri yang berhubungan dengan interaksi siswa pada LMS. Pemodelan dilakukan dengan menerapkan tiga jenis ensemble machine learning yaitu ; bagging, boosting dan voting. Hasil penelitian menunjukkan bahwa model ensemble machine learning yaitu bagging, boosting dan voting berhasil digunakan untuk memprediksi kinerja siswa dengan accuracy sebesar 81.25% dengan percision 0.810, recall 0.812 dan f-measure 0.809 yang diperoleh model bagging. Temuan pada penelitian ini adalah ensemble machine learning dapat diterapkan sebagai model prediks kinerja siswa berdasarkan data Log LMS. Institusi pendidikan baik sekolah maupun perguruan tinggi diharapkan dapat merancang sebuah kurikulum LMS untuk meningkatkan kualitas akademik institusi tersebut. Selain itu institusi pendidikan dapat memprediksi bagaimana kinerja siswanya, sehingga dapat meningkatkan prestasi akademik.

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Published

2024-01-22

How to Cite

Ardianti, M., Nurhayati, O. D., & Warsito, B. . (2024). Model Prediksi Kinerja Siswa Berdasarkan Data Log LMS Menggunakan Ensemble Machine Learning. JST (Jurnal Sains Dan Teknologi), 12(3), 562–571. https://doi.org/10.23887/jstundiksha.v12i3.59816

Issue

Vol. 12 No. 3 (2023): Oktober

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Articles

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