A Dataset of Textual Functional Requirements for Fried Chicken Processing and Sales Systems and Academic Information Systems

This dataset is compiled to provide structured functional requirements documentation for two system domains that are widely used in Indonesia: processing–sales of geprek chicken, and academic information systems. In the midst of a high requirement for clear documentation of requirements, the availability of public datasets containing functional requirements textually is still very limited. Therefore, this dataset presents 54 lines of data, each containing a complete functional requirement, complete with application attributes, modules, actors, title requirements, text requirements in English, and Indonesian translations. This bilingual presentation makes it easy to use for learning software engineering, SRS creation, and NLP research, such as requirement classification and entity extraction.
Some of the data contains the Geprek Resto Management System, which describes general business processes in the culinary industry, including ordering, food processing, cashier-kitchen synchronization, stock management, transaction recording, and financial statement preparation. Requirements are written based on real-world flows, such as the cashier entering an order, the system sending tickets to the kitchen, the chef updating the order status, raw materials automatically being reduced, and notifications of low stock. The dataset also includes specific conditions, such as order cancellations or out-of-stock, providing a realistic context for developing a small to medium business system.
The other section outlines the functional requirements of the Academic Information System, which encompass core educational processes, including Study Plan Card, lecture schedule management, attendance tracking, assessment, and academic validation. Actors such as students, lecturers, and academic staff are represented through requirements that describe multi-level interactions, for example, validation of course prerequisites, the process of filling in grades, to recording attendance based on lecture sessions. The requirement patterns in this domain exhibit typical educational complexities, such as tiered data structures, time-based rules, and repetitive evaluation mechanisms.
With a consistent table structure and coverage of two different domains, this dataset is a rich resource for requirements engineering research, document analysis automation, and the development and education of restaurant systems. It is hoped that this dataset will encourage digital innovation in culinary SMEs and educational institutions, and also serve as a reference for improving the quality of software requirements documentation.