Sistem Informasi Arsip Berkas Perkara dengan Replikasi Basis Data dan Deteksi Anomali VAE
-
Sepfliana Qethi Jaminda Eka Putri
*
Universitas Negeri Padang, Padang,
Indonesia
- Hadi Kurnia Saputra Universitas Negeri Padang, Padang, Indonesia
- Ahmaddul Hadi Universitas Negeri Padang, Padang, Indonesia
- Delvi Asmara Universitas Negeri Padang, Padang, Indonesia (*) Corresponding Author
Abstract
The management of case-file archives in prosecutorial institutions requires accurate tracking, controlled access, and reliable protection of archival records throughout the pre-prosecution, prosecution, and execution stages. Existing archival procedures rely on retention schedules and access-control mechanisms, but the management and protection of archival information require digital support to improve traceability, data integrity, and resilience against unauthorized activities or data loss. This study develops a case-file archive information system that integrates digital archival metadata with security and data-resilience mechanisms. The proposed system combines two-factor authentication (2FA) using TOTP, Role-Based Access Control (RBAC), SHA-256 cryptographic hashing, immutable audit logs with hash chaining, database replication using a Primary-Replica architecture with Write-Ahead Logging (WAL) streaming, and anomaly detection using a Variational Autoencoder (VAE). The system was developed using an Evolutionary Prototype approach and implemented with Electron, ReactJS, Node.js, PostgreSQL, and PyTorch. Evaluation was conducted in an intranet environment with approximately 100 active users through User Acceptance Testing, API testing, integrity testing, database replication testing, and VAE performance evaluation using Precision, Recall, F1-Score, and AUC-ROC. The results showed that all 13 functional scenarios and 16 API endpoints operated as expected, integrity mechanisms successfully detected all data manipulations in the test data, and database replication was synchronized automatically. The VAE achieved a Recall of 1.0000, F1-Score of 0.8197, and AUC-ROC of 1.0000, while its Precision of 0.6944 indicates that further threshold optimization and model refinement are required to reduce false-positive detections. The system therefore serves as digital support for existing archival procedures rather than replacing established archival practices in prosecutorial institutions.
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