MONITORING DAN PREDIKSI RISIKO KELULUSAN MAHASISWA DENGAN RANDOM FOREST MELALUI IMPLEMENTASI DASHBOARD

Bagus Rahmadani, . (2026) MONITORING DAN PREDIKSI RISIKO KELULUSAN MAHASISWA DENGAN RANDOM FOREST MELALUI IMPLEMENTASI DASHBOARD. Tugas Akhir thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

The high rate of delayed graduation among students in Indonesia underscores the urgent need for a more proactive and data-driven academic monitoring system. This study aims to design and develop the MyPrediction application as a web-based early warning system to predict the risk of delayed graduation among students at UPN "Veteran" Jakarta. The method applied is Random Forest using the CRISP-DM approach, with system development following the RAD methodology. The system is built using a Next.js and FastAPI architecture, equipped with JWT authentication, role-based monitoring dashboards, batch prediction via CSV upload, PDF and Excel export reports, high-risk alerts, and an audit log. Model evaluation results demonstrate excellent performance, with an Accuracy of 99.9%, Balanced Accuracy of 97.8%, F1-Score of 98.7%, and a High Risk Recall of 96.3%. Black Box Testing across 93 scenarios on 14 features confirmed all scenarios performed according to specifications. User Acceptance Testing (UAT) involving three real stakeholders from UPNVJ yielded a Task Success Rate of 100% and a Usability Score of 4.33 out of 5.00 (classified as Very Good), confirming the system's readiness for real-world deployment. MyPrediction is expected to support data-driven strategic decision-making by the BAKK to improve the on-time graduation rate.

Item Type: Thesis (Tugas Akhir)
Additional Information: [No.Panggil: 2310501004] [Pembimbing: Tri Rahayu] [Penguji 1: Nur Hafifah Matondang] [Penguji 2: Rio Wirawan]
Uncontrolled Keywords: Early Warning System, Random Forest, Graduation Prediction, Machine Learning, Academic Monitoring
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Fakultas Ilmu Komputer > Program Studi Sistem Informasi (DIII)
Depositing User: BAGUS RAHMADANI
Date Deposited: 28 Aug 2026 04:00
Last Modified: 28 Aug 2026 04:00
URI: http://repository.upnvj.ac.id/id/eprint/50948

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