WEB BASED OPEN INTELLIGENT JOURNAL SYSTEM APPLICATION

• Main Author: Ramadhani Nugroho, Fitrah
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/85027
• Institution: Institut Teknologi Bandung

Open Journal System (OJS) is an open-source software application to manage and publish scientific journals. OJS has an open access literature that is digital, online, free of charge, and free of most copyright and licensing restrictions. OJS existence as online open access journal management platform does not attract authors in publishing their scientific paper in open access journal. Two main reasons are authors were not familiar enough with open access journals in their field and perceived open access journals in their field to have low impact and prestige. OJS doesn’t have the solution or feature that can address these issues. Therefore, new features are needed in OJS to address this issue. This thesis focuses on the development of new web-based journal management system with the addition of new features, which is journal recommendation system and authors analysis in the form of authors statistics. This journal management system is divided into backend and frontend components. The backend component is divided into two sub-systems, namely the API sub-system and the machine learning sub-system for the journal recommendation system. The result from this thesis is journal management website with journal recommendations system and author analysis. Testing was carried out using unit testing and system testing. In addition, the journal recommendation model was evaluated using four metrics, that is accuracy, precision, recall, and f1-score. Test and evaluation results show that journal management system has met the necessary requirements. The journal recommendation feature able to recommend journal to authors with 57 % accuracy and the author analysis feature able to show researchers statistic to visitors.