Irhamni Ali

Literacy development constitutes a central pillar of human capital formation and remains a persistent priority within educational systems and public policy agendas worldwide. Governments continue t...

Selecting an ideal library ambassador for social inclusion requires assessing the key personality traits that influence advocacy and engagement effectiveness. This study examines five critical traits—integrity, persuasion, competence, leadership, and connectivity—among 1364 respondents across Indonesia. Using confirmatory factor analysis and structural equation modeling, all of the indicators significantly contributed to their respective factors, with leadership (presentation: β = .513; inspiration: β = .510) and persuasion (sales ability: β = .492) showing the strongest effects. Fuzzy-set qualitative comparative analysis revealed that high-performing ambassadors combine all five traits configuration: 1,1,1,1,1; score: 3.84, while low performers lack leadership and connectivity, which critically reduces effectiveness. Integrity consistently emerged as a foundational trait driving positive outcomes. The study offers an evidence-based framework for ambassador selection, emphasizing leadership, connectivity, and integrity as the key attributes to strengthen advocacy, promote libraries, and advance Indonesia's literacy movement through inclusive community engagement.

The preservation of paper-based cultural heritage materials is a persistent challenge, especially in tropical and resource-limited contexts where environmental and biological stressors accelerate deterioration. This study investigates the application of deep learning to detect early-stage biodeterioration – specifically insect and mold damage – on digitized paper artefacts. A curated dataset of 274 conservation-grade images was annotated into two classes and evaluated using stratified three-fold cross-validation. Four ImageNet-pretrained convolutional neural networks (CNNs) – VGG-16, ResNet-50, ResNet-101, and MobileNet V2 – were benchmarked. While all models achieved comparable mean accuracy (∼0.719), MobileNet V2 delivered a higher weighted F ₁ -score (0.681) and significantly lower training latency outperforming deeper architectures in both efficiency and minority-class detection. This result is particularly relevant for preventive conservation workflows that require rapid identification of rare deterioration events. MobileNet V2’s lightweight architecture also enables potential deployment on edge devices, supporting real-time diagnostics in collection environments with limited computing infrastructure. The findings affirm the viability of compact CNNs for accurate, class-balanced performance under practical constraints. Limitations include a relatively small dataset and controlled imaging conditions, suggesting the need for expanded, multi-institutional corpora and more diverse acquisition scenarios. Future work will incorporate model explainability techniques (e.g., Grad-CAM) and explore transformer-based alternatives. This research contributes a scalable, reproducible AI-based framework for integrating machine learning into digital heritage diagnostics, advancing the intersection of conservation science and library technology.

Background: Reading Ambassadors and Literacy Mothers play a strategic role in enhancing the literacy culture within Indonesian society. Purpose: This study aims to analyze discourse and public perception regarding the roles of Reading Ambassadors and Literacy Mothers using an unsupervised machine learning approach. Research Design: A qualitative research design was applied, utilizing open-ended survey questions to gather public opinion. Study Sample: Data were collected from 1,041 respondents across Indonesia. Data Collection and/or Analysis: The data were gathered through open-ended questions between mid-September and mid-October 2024 as part of a program effectiveness evaluation. Trigram analysis and topic modeling were used to analyze the responses. Results: Findings revealed recurring phrases reflecting public perceptions and expectations of the Reading Ambassador and Regional Literacy Mother programs. Key themes included their impact on literacy improvement and public aspirations for their continued role in promoting literacy. Conclusions: The study provides in-depth insights into public sentiment about these programs, offering data-driven recommendations to strengthen national literacy policies.

The Indonesian constitution provides for welfare and education. To achieve these constitutional mandates, the Indonesian government passed several laws as the foundation for lifelong education, including the Library Act of 2007 and the National Repository Act of 2018. These Acts are the main legal foundation for the National Library of Indonesia (NLI) to create public policies in library service development across Indonesia. This study seeks to understand these laws through Natural Language Processing (NLP) and Latent Dirichlet allocation (LDA) Topic Modelling. Using these methods, we uncovered the major themes of these legal mandates for library services. Our research revealed five topics for each law. We then analyzed the NLI budgets from 2021 to 2023 to see how the key legal mandates were implemented. We found greater implementation of the 2007 Act than the 2018 Act. Our study offers new methods for library law and policy research.

This research aims to analyze the development of the ChatGPT topic in the context of its utilization and the challenges in supporting 21st-century education and learning programs that require the development of learning media as well as mapping the risks associated with the presence of AI (Artificial Intelligence) phenomenon, specifically ChatGPT. This requires the development of learning media as well as the mapping of risks associated with the presence of AI phenomenon, specifically ChatGPT. The method used in this study is a literature review related to ChatGPT, gathered from the Google database using the Google Advanced search strategy. The keywords "ChatGPT," "education," and "learning" were used to access various publications, particularly national and international scholarly articles that discuss relevant topics. The research findings generally indicate that ChatGPT is currently popular and dynamic, and it is predicted to continue growing in the future. However, discussions specifically related to ChatGPT in the field of education and learning are still the subject of debate, with both supporters and dissenters presenting rational arguments. Several examples demonstrate the significant positive benefits of ChatGPT's presence. To avoid confusion, it is crucial to establish policies formulated by authorized entities and implement them nationally with various supporting regulations.

Purpose: During the COVID-19 pandemic, in order to prevent the spread of disease, the National Library of Indonesia Cataloging Department adopted remote working. There is a need to examine the productivity of remote cataloging as this form of cataloging becomes more prevalent.Design/methodology/approach: The study was conducted using a mixed methods approach. The authors analyzed data to assess cataloging librarians' productivity based on system logs. Then, the authors interviewed librarians to understand librarians' perspectives concerning productivity and remote cataloging, and also to seek insights into factors that may affect productivity while working remotely.Findings: The analysis found higher productivity in terms of quantity of cataloging. Librarians' productivity during remote cataloging is not statistically related to individual factors of age, years of experience, or gender. The in-depth interviews found that other factors may hinder the quality and quantity of the remote cataloging, including the working environment, infrastructure, and lack of policies on remote working.Research limitations/implications: The findings were based on a study conducted in the National Library of Indonesia, which may not apply to libraries with different infrastructures or existing policies in remote cataloging. However, the authors identified numerous factors that could be related to remote cataloging productivity. More work needs to be done to identify these factors that impact productivity by conducting further surveys.Practical implications: The research provides evidence showing the productivity of cataloging can be higher in remote working mode. The study provides insights for library managers to decide whether to implement remote cataloging and what additional perspectives could be considered for the better implementation of remote cataloging.Originality/value: The gap in the literature about remote cataloging and productivity has been bridged.