Pemanfaatan Artificial Intelligence (AI) dalam Visualisasi Data Perpustakaan Universitas Lancang Kuning
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Abstract
Artificial Intelligence (AI) has a significant influence in various aspects. One of the impacts is the library. AI can be applied in various activities, such as data visualization, analysis of library usage trends, book recommendations based on user preferences, and predictions of future collection needs. It is hoped that the Lancang Kuning University Library can be more responsive to user needs and be able to provide excellent service. The method used is descriptive analysis. It aims to find factually relevant facts through data that is collected, processed, and analyzed. The steps of the method taken in the study are problem determination, literature study, data collection, data processing, data implementation, and data analysis. This study produces a description of the stages of library data visualization. There are three stages of library data visualization activities, namely; first, the database preparation stage, this stage is to prepare the dataset taken from SLiMS and service data; second, data processing, this activity is carried out for data filtering, then the data is stored in .xls file format before finally being visualized using Google Looker Studio. Third, visualizing data, data visualization using Google Looker Studio. Lancang Kuning University has initiated the implementation of AI in library data visualization. One of the initiatives is the development of an interactive dashboard that displays statistics on the use of library services in real time. This dashboard allows library managers to easily monitor book loans, daily visits, and other activities. The use of Artificial Intelligence (AI) technology for data visualization at the Lancang Kuning University Library is very significant in increasing the efficiency and effectiveness of information management in the form of statistics. By utilizing AI technology, libraries can present data more interactively and informatively, making it easier for users to access and understand the information available. This also helps library managers in monitoring and analyzing library usage, so that managers can make more informed decisions in developing collections and services.
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References
Asemi, A., Ko, A., & Nowkarizi, M. (2021). Intelligent libraries: a review on expert systems, artificial intelligence, and robot. Library Hi Tech, 39(2), 412-434. DOI 10.1108/LHT-02-2020-0038
Chen, X., Li, Y., & Liu, J. (2020). AI-powered data visualization for libraries: Enhancing user experience through intelligent interfaces. Journal of Library and Information Science, 45(3), 321-340. DOI 10.1108/LHTN-08-2024-0142
Chen, X., & Chen, X. (2021). Data visualization in smart grid and low‐carbon energy systems: A review. International Transactions on Electrical Energy Systems, 31(7), e12889. DOI: 10.1002/2050-7038.12889
Eiriemiokhale, K. A., & Sulyman, A. S. (2023). Awareness and perceptions of artificial intelligence among librarians in university libraries in Kwara State, Nigeria. Indonesian Journal of Librarianship, 4(2), 107-118. DOI 10.33701/ijolib.v4i2.3364
Few, S. (2013). Data Visualization for Human Perception. O'Reilly Media.
Firat, E. E., Joshi, A., & Laramee, R. S. (2022). Interactive visualization literacy: The state-of-the-art. Information Visualization, 21(3), 285-310. DOI 10.1177/14738716221081831
Fu, P., Liu, H., & Wang, Y. (2018). The application of AI in library cataloging. Library Management, 39(2), 134-145.
García-Silva, A., Tarjan, A., & Villegas, A. (2019). User behavior analysis in libraries using AI. International Journal of Library Science, 34(1), 89-102. DOI:10.3233/FAIA230881
Hamad, F., Fakhuri, H., & Abdel Jabbar, S. (2022). Big data opportunities and challenges for analytics strategies in Jordanian academic libraries. New Review of Academic Librarianship, 28(1), 37-60. DOI 10.1080/13614533.2020.1764071
Jia, L., Wang, M., & Zhao, H. (2021). Predictive analytics in libraries: Opportunities and challenges. Library Trends, 69(4), 549-568. DOI 10.21037/atm.2019.10.97
Kato, A., Kisangiri, M., & Kaijage, S. (2021). A review development of digital library resources at university level. Education Research International, 2021(1), 8883483. DOI 10.1155/2021/8883483
Liu, A., Mahapatra, R. P., & Mayuri, A. V. R. (2023). Hybrid design for sports data visualization using AI and big data analytics. Complex & Intelligent Systems, 9(3), 2969-2980. DOI 10.1007/s40747-021-00557-w
Marr, B. (2018). Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things. Kogan Page Publishers. https://books.google.co.id/books/about/Data_Strategy.html?id=nfBVvgAACAAJ&redir_esc=y
Narendra, A. P., Dewi, C., Gunawan, L. S., & Ardi, A. S. (2025). Artificial Intelligence Implementation in Library Information Systems: Current Trends and Future Studies. Vietnam Journal of Computer Science, 1-25. DOI 10.1142/S2196888824300023
Rahmatullah, A. S., Mulyasa, E., Syahrani, S., Pongpalilu, F., & Putri, R. E. (2022). Digital era 4.0: The contribution to education and student psychology. Linguistics and Culture Review, 89-107. DOI 10.21744/lingcure.v6nS3.2064
Raj, R., & Kos, A. (2023). Artificial Intelligence: Evolution, Developments, Applications, and Future Scope. Przeglad Elektrotechniczny, 99(2). DOI 10.15199/48.2023.02.01
Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Prentice Hall. http://repo.darmajaya.ac.id/4836/1
Sarker, I. H. (2022). AI-based modeling: techniques, applications and research issues towards automation, intelligent and smart systems. SN computer science, 3(2), 158. DOI 10.1007/s42979-022-01043-x
Vinothkumar, J., & Karunamurthy, A. (2023). Recent advancements in artificial intelligence technology: trends and implications. Quing: International Journal of Multidisciplinary Scientific Research and Development, 2(1), 1-11. DOI 10.54368/qijmsrd.2.1.0003
Wang, L., Zhang, T., & Chen, H. (2019). Real-time data visualization in libraries using AI-driven dashboards. Library Hi Tech, 37(2), 223-238. DOI:10.1007/978-3-030-82763-2_17
Winata, A. P., Fadelina, R., & Basuki, S. (2021). New normal and library services in Indonesia: A case study of university libraries. Digital Library Perspectives, 37(1), 77-84. DOI 10.1108/DLP-07-2020-0059