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All Journal Khizanah al-Hikmah : Jurnal Ilmu Perpustakaan, Informasi, dan Kearsipan Al-Kuttab : Jurnal Kajian Perpustakaan, informasi dan kearsipan
Sumarsono, Sigit
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Library & Information Science

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Artificial Intelligence in Recordkeeping: A Systematic Review of Machine Learning Applications for Automated Records Classification Sumarsono, Sigit; Wibowo, Muhamad Prabu
Khizanah al-Hikmah : Jurnal Ilmu Perpustakaan, Informasi, dan Kearsipan Vol 13 No 1 (2025): June
Publisher : Program Studi Ilmu Perpustakaan UIN Alauddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/v13i1a12

Abstract

This study presents a systematic literature review (SLR) of scholarly research published between 2014 and 2023, with the aim of identifying prevailing trends, methodological approaches, and contextual factors surrounding the use of Machine Learning (ML) models for records classification within Records Management and Archival Science. Employing the PRISMA framework, the review analyzes a curated selection of studies to assess the scope and maturity of ML applications in this domain. The findings revealed that while ML has been increasingly explored for tasks such as classification and appraisal, its application remains geographically skewed, with the majority of studies originating from Global North countries. The models employed range from probabilistic and regression-based algorithms to decision tree classifiers, reflecting diverse but largely traditional methodological approaches. The adoption of more sophisticated techniques, including deep learning and large language models, was still limited. The study underscores a critical research gap concerning the implementation of advanced ML models, particularly in the context of Global South institutions, where such technologies could significantly enhance recordkeeping efficiency and scalability. This review highlights the need for further empirical studies that develop and evaluate cutting-edge ML models in diverse archival contexts, promoting more inclusive and globally representative innovation in archival automation.
Kapabilitas preservasi arsip elektronik pada infrastruktur pembelajaran Kemenkeu Learning Center Sumarsono, Sigit; Lawanda, Ike Iswary
Al-Kuttab : Jurnal Kajian Perpustakaan, Informasi dan Kearsipan Vol 6, No 2 (2024): Al-Kuttab: Jurnal Kajian Perpustakaan, Informasi dan Kearsipan
Publisher : Universitas Islam Negeri Syekh Ali Hasan Ahmad Addary Padangsidimpuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24952/ktb.v6i2.11302

Abstract

Kemenkeu Learning Center (KLC) merupakan aplikasi yang mengelola arsip dan konten digital sebagai konsekuensi dari proses bisnis yang dijalankan. Untuk itu, evaluasi perlu dilakukan untuk melihat kapabilitas aplikasi dalam memelihara dan melestarikan keutuhan dan autentisitas arsip yang tercipta selama daur hidup arsip. Penelitian terhadap kapabilitas organisasi dan layanan dilakukan dengan menggunakan Digital Preservation Coalition Rapid Assessment Model (DPC RAM) sebagai kerangka penilaian kapabilitas. Hasil penelitian menunjukkan bahwa infrastruktur dan proses bisnis dalam KLC telah memenuhi kapabilitas dalam pelestarian arsip digital khususnya terkait kelangsungan organisasi, kebijakan dan strategi, legal dan etis, serta manajemen metadata. Preservasi arsip pada KLC juga memiliki keunggulan dalam hal kapabilitas teknologi informasi, proses akuisisi dan transfer, preservasi bitstream, hingga proses penemuan dan akses. Meski demikian, kelemahan masih ditemukan dalam hal perbaikan berkelanjutan, komuniatas, serta preservasi konten. Penelitian ini menunjukkan kemampuan DPC RAM sebagai model penilaian preservasi arsip yang menyeluruh dari segi organisasi maupun infrastruktur teknologi.
Co-Authors Ike Iswary Lawanda Wibowo, Muhamad Prabu