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Feb 25, 2025
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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.

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How to Cite
Adriano, R., Concepcion, A. U., Cruz, M. M. S., & Concepcion, A. T. V. (2025). A Segmentation Analysis Utilizing Natural Language Processing Model with Interactive Data Analytics Dashboard for Research Management Platform. International Journal of Multidisciplinary: Applied Business and Education Research, 6(2), 892-904. https://doi.org/10.11594/ijmaber.06.02.31

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