Purpose. The project intends to use a qualitative approach to investigate the state and procedures of present transaction processes to pinpoint inefficiencies. Integrating ICT and coding solutions will be formulated and examined through prototyping to evaluate their feasibility and effectiveness. By concentrating on user behaviour and section-specific dynamics, the study offers a more analytical and data-driven approach to library management by leveraging Python's analytical capabilities and extracting quantitative data from transaction logs. Future funding can be directed towards required and necessary subjects by using library management's data to research trends and student requirements. This research can potentially transform library operations and ultimately enhance everyone's user experience for all.

Methodology. The approach entails the utilization of ICT and programming to conduct a qualitative examination of data about the transaction aspects of publications.

Results and discussion. By utilising ICT and coding, publication transaction data is consolidated efficiently in the preferred format, paving the way for advanced analytics and strategic insights with minimal human input.

Conclusions. This study contributes to the examination, implementation, and consolidation of automated transaction recording across various sections of a library, with a prospective expansion towards integration with library management systems such as KOHA, Evergreen, Easylib, and Software for University Libraries (SOUL).