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All Journal JIPI (Jurnal Ilmu Perpustakaan dan Informasi) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) SKANIKA: Sistem Komputer dan Teknik Informatika
Sherly Rosa Anggraeni
Universitas Negeri Malang
Computer Science & IT Control & Systems Engineering Education Engineering Library & Information Science

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DIGITAL LITERACY CAMPAIGN AND PUBLIC INFORMATION BEHAVIOR CHANGE: A CASE OF OPAC USE Sherly Rosa Anggraeni; Tsabitah Tifali Dhiyaulhaq; Putri Shofura; Sabrina Bunga Cantika; Yeremia Rizky Paramasatya
JIPI (Jurnal Ilmu Perpustakaan dan Informasi) Vol 10, No 2 (2025)
Publisher : Progam Studi Ilmu Perpustakaan UIN Sumatera Utara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/jipi.v10i2.26571

Abstract

This study aims to evaluate the effectiveness of a digital literacy campaign based on video and booklet media in improving the public's understanding and skills in using the Online Public Access Catalog (OPAC) at the Malang City Library. The study addresses the gap between OPAC service availability and users' limited digital literacy, which hinders optimal utilization of library technologies. Data were collected from 136 respondents representing diverse demographic backgrounds. A mixed-method pre-test and post-test design was applied to measure changes in knowledge, attitudes, and OPAC use, complemented by thematic analysis of interviews. The results show a significant improvement in users' OPAC knowledge and their ability to conduct independent searches after the campaign. Confidence and perceived ease of use also increase, accompanied by a notable reduction in perceived technical barriers. Qualitative findings strengthen these results by confirming that video and booklet media help simplify OPAC usage and make users more prepared to adopt digital services. Overall, the campaign demonstrates effectiveness as a targeted intervention that supports behavioral change toward technology-based information seeking. These findings highlight the importance of continuous user education, strengthened digital literacy, and accessible guidance materials for sustaining the digital transformation of public library services.
Implementasi Algoritma Clustering DBSCAN terhadap Pola Navigasi Pengguna di Perpustakaan Digital untuk Mengungkap Zona Buta Akses Informasi dan Optimalisasi Antarmuka Sistem Sherly Rosa Anggraeni
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 8 No 2 (2025): Jurnal SKANIKA Juli 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v8i2.3524

Abstract

Advances in information technology have encouraged the transformation of libraries to digital form, increasing accessibility, but not all collections can be reached equally by users. This study aims to identify user navigation patterns and information access blind zones in the INLISLite digital library system using the DBSCAN clustering algorithm. Simulation log data representing common user exploration sessions were analyzed through the stages of one-hot representation, density-based clustering, and two-dimensional visualization with PCA. The results showed the formation of six main clusters with different navigation behavior characteristics and 15% of the sessions were classified as outliers. Pages such as “Advanced Search” and “Favorites” were detected as blind zones because they were not reached in most sessions. These findings indicate a failure of the interface to bridge users to the entire spectrum of information. Recommendations of navigation redesign, contextual pop-up of hidden content, and adaptive interface approaches were proposed as solutions. The DBSCAN-based approach proved effective for evaluating the effectiveness of digital information systems in terms of user behavior, and has the potential to be applied in the development of more responsive and inclusive digital libraries.
TOPIC MODELING OF UNDERGRADUATE THESES METADATA USING LDA FOR TREND ANALYSIS IN LIS Sherly Rosa Anggraeni; Moh Safii; Rani Auliawati Rachman; Amalia Nurma Dewi
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 4 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i4.9330

Abstract

Uncovering latent trends in academic metadata is critical for under-standing research dynamics in information systems. This study em-ploys Latent Dirichlet Allocation (LDA), a probabilistic machine learning algorithm in artificial intelligence, to analyze metadata from 180 undergraduate theses (2020–2024) at Universitas Negeri Malang, using Library and Information Science (LIS) as a case study. The da-taset, comprising titles and abstracts, underwent preprocessing (tokeni-zation, lowercasing, stopword removal, and domain-specific term fil-tering) to create a clean text corpus. Using Gensim’s variational Bayes, LDA models with K=5–15 topics were tested, selecting K=8 based on optimal C_v coherence (0.65) and perplexity (~150). Topics, labeled via top keywords, include Digital Libraries, User Behavior, and Ar-chive Management. Annual topic distributions, visualized via stacked bar charts, revealed a surge in digital topics during 2021–2022 (pan-demic-driven) and rising user behavior focus in 2022–2023. This LDA framework demonstrates scalability for text mining in academic data-bases, offering a replicable pipeline for trend analysis across domains like education or social media. Findings complement global studies, providing insights for curriculum alignment. Limitations include small dataset size and metadata-only analysis. Future work could integrate full-text data or advanced models like BERTopic for enhanced seman-tic discovery.
Co-Authors Amalia Nurma Dewi Moh. Safii Putri Shofura Rani Auliawati Rachman Sabrina Bunga Cantika Tsabitah Tifali Dhiyaulhaq Yeremia Rizky Paramasatya