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All Journal Jurnal Teknik Informatika (JUTIF) Jurnal Abdi Masyarakat Indonesia
Arif Rohmadi, Arif
Universitas Gadjah Mada
Humanities Computer Science & IT Economics, Econometrics & Finance Education Engineering Public Health

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Comparative Analysis of Machine Learning Algorithms with RFE-CV for Student Dropout Prediction Utami, Sekar Gesti Amalia; Setiadi, Haryono; Rohmadi, Arif
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 3 (2025): JUTIF Volume 6, Number 3, Juni 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.3.4695

Abstract

The high dropout rate of students in higher education is a problem faced by educational institutions, impacting quality assessments and accreditation evaluations by BAN-PT. This study aims to develop an early prediction model of potential dropout students using demographic data with a learning analytics approach. Five classification algorithms are used in this research, namely Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), Light Gradient Boosting Machine (LGBM), and Support Vector Machine (SVM). The dataset used consists of undergraduate student data of Sebelas Maret University in 2013 (n=2476) which is processed through preprocessing techniques, resampling with SMOTE, and validation using K-Fold Cross-Validation. The results showed that the RF model gave the best performance with an accuracy of 96.01%, followed by LGBM (95.26%), DT (91.24%), LR (83.68%), and SVM (83.19%). The use of the Recursive Feature Elimination with Cross-Validation (RFE-CV) feature selection method was able to improve the efficiency of the model by reducing the number of features without significantly degrading performance. The best feature selection was obtained when using 75% features, which provided an optimal balance between the number of features and model accuracy. The most contributing features include IPS_range (Semester GPA range), parents' income, students' regional origin, as well as several other demographic factors. This study contributes to the development of early warning systems in higher education by providing accurate predictive models and identifying key risk factors.
Peningkatan Kualitas Administrasi Pendidikan melalui Implementasi Sistem Edu Berbasis ERP di SMP IT Insan Mulia Surakarta, Jawa Tengah Widoyono, Bambang; Saptono, Ristu; Rohmadi, Arif; Syaifuddin, Akhmad; Hendra, Brilyan; Anggoro, Rizal Dwi; Ibrahim, Muhammad Syafiq
Jurnal Abdi Masyarakat Indonesia Vol 5 No 6 (2025): JAMSI - November 2025
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54082/jamsi.2130

Abstract

SMP Islam Insan Mulia Surakarta-Jawa Tengah, mengalami kendala administrasi akibat sistem manualnya, terutama dalam penerimaan siswa baru (PPDB), pencatatan pembayaran, dan pengelolaan bank soal. Kendala-kendala ini menyebabkan keterlambatan, kesalahan, dan inefisiensi, sehingga membatasi kualitas layanan. Untuk mengatasi hal ini, dalam program pengabdian masyarakat kami mengimplementasikan sistem EDU berbasis ERP sebagai solusi terintegrasi. Sistem ini menggunakan model waterfall untuk analisis, perancangan, implementasi, pelatihan, dan pengujian yang diterapkan selama tiga bulan. Tiga modul diimplementasikan: PPDB, pembayaran, dan bank soal, yang diuji coba kepada 23 peserta. Evaluasi menunjukkan hasil positif dengan efisiensi (4,08), efektivitas (4,08), dampak (4,38), kepuasan (4,28), dan kemudahan penggunaan (4,17) pada rentang skala 1-5. Program pengabdian ini tidak hanya menyelesaikan kendala administratif di SMP Islam Insan Mulia Surakarta, tetapi juga menghadirkan model implementasi sistem informasi berbasis ERP yang dapat direplikasi di sekolah lain. Digitalisasi administrasi melalui modul PPDB, pembayaran, dan bank soal terbukti meningkatkan efisiensi, transparansi, dan profesionalisme tata kelola pendidikan secara umum.
Co-Authors Anggoro, Rizal Dwi Hendra, Brilyan Ibrahim, Muhammad Syafiq Ristu Saptono Setiadi, Haryono Syaifuddin, Akhmad Utami, Sekar Gesti Amalia Widoyono, Bambang