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All Journal International Journal of Multidisciplinary: Applied Business and Education Research
Cruz, Marian Minneli S.
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Environmental Science Medicine & Pharmacology

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A Segmentation Analysis Utilizing Natural Language Processing Model with Interactive Data Analytics Dashboard for Research Management Platform Adriano, Raquel; Concepcion, Anthony U.; Cruz, Marian Minneli S.; Concepcion, Alaina Thea V.
International Journal of Multidisciplinary: Applied Business and Education Research Vol. 6 No. 2 (2025): International Journal of Multidisciplinary: Applied Business and Education Rese
Publisher : Future Science / FSH-PH Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/ijmaber.06.02.31

Abstract

Research is a vital component of a university and, currently, unstruc-tured big data is a significant issue in various ICT industries and insti-tutions. To solve this modern problem, the researchers developed a system to streamline the manual operations and traditional research management system of the university through Natural Language Pro-cessing (NPL). This quantitative research utilizing descriptive-developmental design is about designing and evaluating A Segmenta-tion Analysis Utilizing Natural Language Processing Model with In-teractive Data Analytics Dashboard for Bulacan State University Re-search Management Platform utilizes the framework of progressive prototyping in the development process. Consultative meetings, in-terviews and the use of survey questionnaires were held to obtain data from ten (10) RDO/CDRU and staff, twenty (20) IT experts and twenty (20) academicians were chosen using random sampling. Re-sults show that personalize learning management system is excellent in terms of functional suitability (M=4.66), performance efficiency (M=4.68), compatibility (M=4.67), usability (M=4.74), reliability (M=4.51), security (M=4.44), maintainability (M=4.72), and portabil-ity (M=4.65). Subsequently, the developed system recorded a grand mean of 4.63 interpreted as Excellent among all ISO/IEC 25010 crite-ria. This indicates that the system complies with end-user needs as well as software quality standards. It is therefore prepared for adop-tion. Along with its implementation, it is recommended to gather feedback regularly and conduct an impact analysis of the effective-ness of using the segmentation analysis utilizing natural language processing model with interactive data analytics dashboard for re-search management platform.
Co-Authors Adriano, Raquel Concepcion, Alaina Thea V. Concepcion, Anthony U.