A rule-based checklist recommender system for UiTM community project evaluation

Currently, Sistem PRIMe is a platform primarily used for project documentation and submission. The system is used to evaluate community projects at Universiti Teknologi MARA (UiTM). However, because the system does not offer direct feedback before project registration, many projects have low to moderate star ratings and are often resubmitted as a result of insufficient documentation and non-compliance with the evaluation requirements specified in the Manual Libatsama 2024. To assist lecturers and project coordinators in reviewing community projects before register the projects in Sistem PRIMe this project proposes a rule-based checklist recommender system. A rule-based inference engine, using predefined “If-Then” rules derived from the Manual Libatsama 2024, evaluates checklist fulfilment and determines an appropriate star rating, along with actionable recommendations for improvement. The system was developed using the Agile methodology and implemented with HTML, CSS, JavaScript, PHP, and MySQL. Testing was carried out to validate functional Functional, unit, integration, and validation testing were conducted to assess the functionality and consistency of the developed system. It is expected that this project will minimize the need for manual review, assist lecturers and project coordinators in evaluating community projects with required criteria before register into Sistem PRIMe and enhance the overall quality and star-rating performance of community projects at UiTM.