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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

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.

Identifying Research Trends and Gaps in the Context of Linux and Unix Security Adriano, Raquel C.; Calayag, Jahleine Marielle M.; Cruz, Marian Minelli S.; Concepcion, Anthony U.
International Journal of Multidisciplinary: Applied Business and Education Research Vol. 6 No. 6 (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.06.06.14

Linux and Unix operating systems are fundamental to modern computing infrastructures, including cloud platforms, mobile devices, and supercomputers. With their increasing adoption, security has remained a persistent and evolving concern over the past two decades. This study conducts a systematic bibliometric analysis of 50 peer-reviewed journal articles and conference papers published between 2001 and 2020, segmented into four time periods: 2001–2005, 2006–2010, 2011–2015, and 2016–2020. Using citation analysis and co-word mapping via Mendeley and VOSviewer, the study identifies four main thematic clusters: (1) access control and authentication, (2) kernel-level vulnerabilities, (3) cloud and container security, and (4) mobile and Android-related threats. Early research focused on foundational topics such as system architecture and access control mechanisms, while more recent studies emphasized cloud-native security, virtualization, and mobile platform vulnerabilities. The analysis also reveals a significant disparity in research volume, with Linux-related studies dominating the field and Unix security receiving less than 20% of the total focus. This underrepresentation of Unix indicates a critical gap in the literature. These findings highlight not only the shifting priorities in open-source operating system security but also the need for renewed attention to Unix-specific threats and cross-platform security strategies in future research.

Smart Queuing and Appointment Management System for Client Services in Bulacan State University Bustos Campus Concepcion, Alaina Thea V.; Concepcion, Anthony U.; Guinto, Clarisse Ann A.; Araza, Christian; Imperio, Rhye Dayrone H.; Regaas, Beverly; Perez, Nino Marine N.
International Journal of Multidisciplinary: Applied Business and Education Research Vol. 7 No. 1 (2026): 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.07.01.02

Client service efficiency has been a key issue in academic institutions as the rise in student populations overburdens the administrative functions of institutions. To eliminate the issues of manual queuing and appointment systems, this paper has developed the Smart Queuing and Appointment Management System, the web-based system that targets the administration of Bulacan State University -Bustos Campus. The system is expected to simplify the flow of clients, decrease waiting time and improve service delivery by using automated queue management, online scheduling and real time monitoring of transactions. The project was designed in HTML, CSS, JavaScript, PHP, and MySQL and adhered to the Agile Software Development Life Cycle (SDLC) to guarantee iterative user-driven enhancement of the project. To measure the performance and acceptability of the system, the Technology Acceptance Model (TAM) and the ISO/IEC 25010:2023 Software Quality Standards were used, and the techniques were functionality, usability, reliability, and efficiency. The evaluation involved 50 respondents, who were recorded in terms of surveys and interviews, and they were a combination of students, administrative staff, and IT specialists. The result showed that the system had a general weighted mean of 4.59 according to ISO/IEC 25010, which is interpreted as Strongly Agree, and this shows a high-quality functionality, reliability and usability. Under TAM, the responses of staff and students were very positive and the weighted means of responses were 4.84 and 4.45, respectively. These findings indicate that the system is successfully used to increase administrative efficiencies, reduce congestion as well as client satisfaction.

Chatbot AWARE: A Thematic Literature Review on Chatbot Awareness, Workload-Based Adoption, Responsibility, and Ethics in Higher Education Institutions Concepcion, Anthony U.
International Journal of Multidisciplinary: Applied Business and Education Research Vol. 7 No. 1 (2026): 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.07.01.28

AI chatbots may improve learning, simplify teaching, and engage students at colleges and institutions. AWARE examined chatbots' effects on instructors and students. Awareness, ethics, responsibility, and workload-based adoption comprise the framework. By reviewing 19 scholarly sources, the researchers created the AWARE framework. Topics were sorted into four groups. Researchers ought to know the framework's pros and cons and smart uses. Online chatbots can teach, administer, and collect feedback, according to the study. There are however some problems, like lower emotional intelligence, the risk of disseminating false information, concerns about academic honesty, and the fact that not everyone can access the material. The study shows that chatbots can help with teaching instead of replacing it, as long as there are clear rules and a consistent way of teaching. The lack of lasting empirical evidence concerning the effectiveness of chatbots highlights the imperative for subsequent research aimed at measurable learning outcomes, equitable access, and the establishment of stringent ethical standards for AI integration in higher education.

Smart Queuing and Appointment Management System for Client Services in Bulacan State University Bustos Campus Concepcion, Alaina Thea V.; Concepcion, Anthony U.; Guinto, Clarisse Ann A.; Araza, Christian; Imperio, Rhye Dayrone H.; Regaas, Beverly; Perez, Nino Marine N.
International Journal of Multidisciplinary: Applied Business and Education Research Vol. 7 No. 1 (2026): 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.07.01.02

Client service efficiency has been a key issue in academic institutions as the rise in student populations overburdens the administrative functions of institutions. To eliminate the issues of manual queuing and appointment systems, this paper has developed the Smart Queuing and Appointment Management System, the web-based system that targets the administration of Bulacan State University -Bustos Campus. The system is expected to simplify the flow of clients, decrease waiting time and improve service delivery by using automated queue management, online scheduling and real time monitoring of transactions. The project was designed in HTML, CSS, JavaScript, PHP, and MySQL and adhered to the Agile Software Development Life Cycle (SDLC) to guarantee iterative user-driven enhancement of the project. To measure the performance and acceptability of the system, the Technology Acceptance Model (TAM) and the ISO/IEC 25010:2023 Software Quality Standards were used, and the techniques were functionality, usability, reliability, and efficiency. The evaluation involved 50 respondents, who were recorded in terms of surveys and interviews, and they were a combination of students, administrative staff, and IT specialists. The result showed that the system had a general weighted mean of 4.59 according to ISO/IEC 25010, which is interpreted as Strongly Agree, and this shows a high-quality functionality, reliability and usability. Under TAM, the responses of staff and students were very positive and the weighted means of responses were 4.84 and 4.45, respectively. These findings indicate that the system is successfully used to increase administrative efficiencies, reduce congestion as well as client satisfaction.

Chatbot AWARE: A Thematic Literature Review on Chatbot Awareness, Workload-Based Adoption, Responsibility, and Ethics in Higher Education Institutions Concepcion, Anthony U.
International Journal of Multidisciplinary: Applied Business and Education Research Vol. 7 No. 1 (2026): 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.07.01.28

AI chatbots may improve learning, simplify teaching, and engage students at colleges and institutions. AWARE examined chatbots' effects on instructors and students. Awareness, ethics, responsibility, and workload-based adoption comprise the framework. By reviewing 19 scholarly sources, the researchers created the AWARE framework. Topics were sorted into four groups. Researchers ought to know the framework's pros and cons and smart uses. Online chatbots can teach, administer, and collect feedback, according to the study. There are however some problems, like lower emotional intelligence, the risk of disseminating false information, concerns about academic honesty, and the fact that not everyone can access the material. The study shows that chatbots can help with teaching instead of replacing it, as long as there are clear rules and a consistent way of teaching. The lack of lasting empirical evidence concerning the effectiveness of chatbots highlights the imperative for subsequent research aimed at measurable learning outcomes, equitable access, and the establishment of stringent ethical standards for AI integration in higher education.

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