TLA Research Journal

Data Analysis for Waste Classification Using Image Processing Techniques of the Office of Academic Resources, Prince of Songkla University

Komgrit Rumdon — Tue, 03 Mar 2026 00:00:00 +0700

This research aims (1) to analyze data for classification of waste images using image processing techniques and (2) to measure the efficiency and accuracy of waste image classification using image processing techniques using the Teachable Machine tool that uses the principles of Machine Learning (ML) to automatically classify waste images. The data used were 250 of 2D vector images of waste, divided into 200 images for learning (Train set) and 50 images for testing (Test set) in a ratio of 80:20. The results of the accuracy measurement found that the overall accuracy was 95.72%. When classifying the accuracy of each type of waste image, it was found that the hazardous waste image had the highest accuracy (99.10%), followed by infectious waste (96.60%), general waste (95.30%), recycled waste (95.10%), and organic waste had the lowest accuracy (92.50%). Data analysis for waste classification using image processing techniques can be developed into a waste sorting system application for use in libraries and various agencies, including for using innovations for energy and environmental conservation activities and supporting the operations of the Green Office and Green Library in using tools to provide knowledge about waste classification to people in the community to be aware of effective waste management.

A Data-Driven Analysis of Library User Segmentation through the CRISP-DM Framework

Pandaree Soonthonwarapas — Tue, 03 Mar 2026 00:00:00 +0700

The purpose of this study was to analyze and segment library users using a data-driven approach by applying the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. The CRISP-DM framework consists of six phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The dataset used in this study comprises 35,242 transaction records of information resource borrowing from the Khunying Long Athakravisunthorn Learning Resources Center, Prince of Songkla University, Hat Yai Campus, covering the period from January 1 to December 31, 2024. Data analysis was conducted using KNIME analytics software, employing the RFM segmentation technique, which is based on three key indicators: Recency (the most recent library usage), Frequency (the number of transactions), and Monetary (the volume of borrowed resources). The data were analyzed across defined time intervals to classify library users into distinct segments according to their usage behaviors. The results demonstrate that the proposed approach effectively identifies clear and meaningful user segments, enabling the library to gain deeper insights into usage patterns, needs, and potential value of different user groups. In addition, the segmentation model allows for the identification of users who are likely to continue using library services as well as those at risk of reduced or discontinued usage in the future. The findings support strategic decision-making in library management, particularly in designing targeted activities, developing user-specific services, and enhancing user relationship management. Ultimately, this data-driven user segmentation approach contributes to improving service effectiveness, increasing user satisfaction, and sustaining long-term library user engagement.

Development of Information System to Support Risk Management: A Case Study of the Faculty of Agriculture, Khon Kaen University

Wed, 01 Apr 2026 00:00:00 +0700

This study aimed to develop an information system to support risk management, using the Faculty of Agriculture, Khon Kaen University, as a case study, and to evaluate user satisfaction with the system. The participants consisted of 30 administrators, staff members, and stakeholders directly involved in the use of the information system for risk management. The developed system was designed and implemented as a web-based platform to facilitate systematic risk management, comprising three main modules: (1) a Risk Management Dashboard, which presents an overview of the organization’s risk status; (2) a Risk Management Plan page, which displays and monitors the progress of action plans to mitigate or control risks; and (3) a Risk Event page, which enables users to record, edit, and manage risk events effectively. The findings revealed that users were highly satisfied with the overall quality and usability of the system ( = 4.54, S.D. = 0.52). Satisfaction with the quality of information and content was rated at a high level ( = 4.46, S.D. = 0.64), while satisfaction with usefulness and applicability reached the highest level ( = 4.60, S.D. = 0.58). Moreover, overall satisfaction and emotional experience were also at the highest level ( = 4.51, S.D. = 0.57). These findings indicate that the developed information system is well-suited for practical use and can effectively support organizational risk management in terms of data visualization, systematic risk operations, and providing a reliable and user-friendly experience.

Digital Services Design for the Faculty of Veterinary Sciences Library, Mahasarakham University

Nuchthana Chaiyotha, Rungtip Charoensak — Thu, 02 Apr 2026 00:00:00 +0700

This study aimed to investigate the problems and needs related to the use of digital library services at the Faculty of Veterinary Science, Mahasarakham University, develop a conceptual framework for designing digital library services as part of a Development of Digital services model for Faculty of Veterinary Sceiences Library Mahasarakham University. The research applied the service design concept from the Thailand Creative & Design Center (TCDC), consisting of 3 key stages: 1) exploration, 2) creation, and 3) Reflection. The qualitative phase involved interviews with 32 participants, including 5 administrators, 20 lecturers, 5 scientists, 1 doctoral student, and 1 master’s student, as well as focus group discussions with 18 undergraduate students (three from each year level, Years 1–6) who were frequent library users. The quantitative phase involved expert evaluation of the digital service application design concept by 3 specialists. The findings revealed that the design of digital library services for the Faculty of Veterinary Sciences was developed through a service workflow diagram that aligned with user needs, encompassing 6 core services: (1) Web OPAC, (2) Online database, (3) Online circulation, (4) Online new books and articles recommendation, (5) Conseling services, and (6) Digital library usage guidance. The evaluation results indicated that the overall suitability of the proposed design was rated at a high level (= 3.95). When considered by aspect, usability received the highest mean score (= 4.08), followed by content quality (= 4.00) and design aesthetics (= 3.77). These findings suggest that the proposed digital service design concept is appropriate, practical, and consistent with user requirements, supporting the advancement of digital library development in higher education institutions.

Factors and Challenges in Integrating Technology into Library Services in School: A Case Study of a University Demonstration School under the Ministry of Higher Education, Science, Research and Innovation

Kaimuk Laosunthara, Ampan Laosunthara — Sat, 04 Apr 2026 00:00:00 +0700

This research investigates the factors and barriers to integrating technology in library services at university demonstration schools under the Ministry of Higher Education, Science, Research and Innovation. Data collected from nine school librarians revealed that the librarian-to-student ratio was 1:726, exceeding standard 1:500, reflecting high workloads for librarians, particularly in schools with ratios above 1:1,000. The study also identified inequalities in personnel allocation even among schools with similar student populations. A significant finding was that students across all schools still preferred borrowing physical books over e-books, despite the digital era. School library development faces numerous challenges, including budget constraints, lack of policy continuity, administrators' limited understanding of digital technology, system and service provider instability, and underappreciation of library importance. Developing effective school libraries requires collaboration among all stakeholders to enable libraries to foster information literacy skills essential for lifelong learning in the 21st century.

User Expression in the Public Space through the Instagram Exchange Board of the Central Library, KMUTNB: A Socio-Communicative Analysis in the Context of the AI-Era University Library

Navarat Phokiew — Sat, 04 Apr 2026 00:00:00 +0700

This study aims to (1) analyze patterns of user expression in the public space of the university library, and (2) examine the role of service innovation as a safe space to address communication challenges in the performance-driven AI era. A mixed-methods research design was employed, integrating quantitative content analysis using descriptive statistics with qualitative interpretation of user-generated content posted on the Instagram Exchange Board named “LibMePlay.” A total of 300 entries were analyzed. Quantitative findings reveal that the primary purpose of user expression focused on identity and self-representation (49.3%), followed by entertainment-seeking (18.7%) and emotional release or stress relief (13.0%). These results align with the observation that most content (65.3%) was non-academic in nature, with a predominantly positive or humorous tone (85.7%). A significant finding is that the majority of users (98.7%) explicitly identified themselves through their personal Instagram usernames or pseudonyms, reflecting a high level of trust in the platform. In conclusion, the “LibMePlay” board successfully functioned as a counter-algorithmic safe space, enabling users to express and construct communicative identities freely and naturally, without pressure from performance metrics or comparative mechanisms. The findings suggest that socially-oriented service innovation is a key strategy for university libraries to promote digital well-being and foster social communities in the age of artificial intelligence

Artificial Intelligence and the Enhancement of Library Science and Information Science: Potential for Sustainable Development

Yuttana Jaroenruen — Tue, 03 Mar 2026 00:00:00 +0700

In the era of digital revolution, where Artificial Intelligence (AI) technology plays a crucial role across all sectors, libraries and library science cannot avoid this major transformation. This article aims to analyze the role of AI technology in transforming the structure and operational models of modern libraries, as well as its connection to the Sustainable Development Goals (SDGs), particularly SDG 4 on quality education and lifelong learning, through a literature review and analysis of global trends.

The study reveals that modern libraries have undergone a significant transformation in their role from single information service providers to integrated information service hubs. AI technology plays a crucial role in developing services across six main areas: 1) automated conversational systems and virtual assistants that provide 24/7 question-answering and user assistance services; 2) intelligent recommendation and discovery systems that analyze user behavior to suggest resources tailored to individual needs; 3) intelligent information search systems that process natural language and provide highly relevant results; 4) security systems that use image and behavior analysis to prevent resource loss; 5) automated cataloging and classification that enhances collection management efficiency; and 6) resource and inventory management covering demand forecasting, reorder point calculation, and multi-branch resource management.

In education, AI technology has demonstrated potential in supporting SDG4 through the development of adaptive learning systems, academic performance prediction systems, educational resource management systems, and data analytics systems for informed educational decision-making. It also supports lifelong learning by providing age-appropriate content adaptation and personalized learning pathways.

The opportunities and challenges arising from implementing AI technology in library work include the potential for librarians to elevate their roles from information custodians to knowledge managers and learning consultants, allowing for more time to develop creative services, and enhanced collaboration with specialists across various fields. The main challenges include developing technological skills, managing change, addressing privacy and data security concerns, and maintaining balance between increased efficiency and preserving human elements in service delivery.