การพัฒนารูปแบบระบบธุรกิจอัจฉริยะเพื่อสนับสนุนการตัดสินใจ การบริหารจัดการรายได้ มหาวิทยาลัยเทคโนโลยีราชมงคลสุวรรณภูมิ
Abstract
The results of the research conducted at Rajamangala University of Technology Suvarnabhumi on the development of a business intelligent system model to support revenue management decision-making can be applied to the design and development of the university's internal information systems. This includes the development of data processing procedures for trend analysis, the facilitation of strategic planning, and efficient revenue management within the university.
Utilising descriptive statistics, including mean and standard deviation, the analysis of the development model's applicability incorporated statistical methods such as the mean and standard deviation. The evaluation of suitability adheres to the Rating Scale Model, which collects data from subject matter experts via questionnaires. These specialists provide their ratings and opinions on various aspects pertaining to the development and implementation of an intelligent business system. By utilising this methodology, the research can gain valuable insights and make informed decisions regarding the efficacy and suitability of the proposed model for facilitating decision-making and revenue management at Rajamangala University of Technology Suvarnabhumi.
According to the findings, the model included 1) system user management, 2) revenue management information, 3) a revenue forecasting management system, and 4) dashboard. With an aggregate mean of 4.67 and a standard deviation of 0.500, the results of the evaluation of the development of the model by nine experts were at the highest level of suitability.
References
M. Safeer and S. Zafar, "Impact of business intelligence competency center in success/failure of B.I. applications," 2011 IEEE 14th
Foley, É., & Guillemette, M. G. (2010). What is business intelligence? International Journal of Business Intelligence Research, 1(4), 1–28. https://doi.org/10.1007/978-1-4302-3325-1_1
Scheierman, L. (2017, June 29). Business intelligence competency centers: Overview and guide. KnowledgeLeader. Retrieved March 10, 2023, from https://info.knowledgeleader.com/
business-intelligence-competency-centers-overview-and-guide
กองนโยบายและแผน. (2565, 22 ตุลาคม). แผนยุทธศาสตร์การเงิน มหาวิทยาลัยเทคโนโลยีราชมงคลสุวรรณภูมิ. https://plan.rmutsb.ac.th/plan/data_information/file/100_PL_891.pdf
Williams, J. R. (2008). Financial & managerial accounting. McGraw-Hill Irwin
Bentley, D. (2017). Business intelligence and analytics. Library Press.
Nogués, A., & Valladares, J. (2017). Business intelligence tools for small companies. Springer.
AskMe Solutions & Consultants. (2023, April 5). Power BI for business intelligence system. https://www.askme.co.th/article/power-bi-business-intelligence/
Llave, M. R. (2018). Data lakes in business intelligence: Reporting from the trenches. Procedia Computer Science, 138, 516–524. https://doi.org/10.1016/j.procs.2018.10.073
Kyaw, K. S., Tepsongkroh, P., Thongkamkaew, C., & Sasha, F. (2023). Business intelligent
framework using sentiment analysis for smart digital marketing in the e-commerce era.
Asia Social Issues, 16(3), e252965. https://doi.org/10.48048/asi.2023.252965
Belesiotis, A., Papadakis, G., & Skoutas, D. (2018). Analyzing and predicting spatial crime
distribution using crowdsourced and open data. ACM Transactions on Spatial Algorithms and Systems, 3(4), Article 12. https://doi.org/10.1145/3190345
Khder, M. A., Abu-Alsondos, I. A., & Bahar, A. Y. (2021). The impact of implementing data mining in business intelligence. International Journal of Entrepreneurship, 25(4S), 1–7.
https://www.abacademies.org/articles/the-impact-of-implementing-data-mining-in- business-intelligence-11473.html
Shmueli, G., Bruce, P. C., & Patel, N. R. (2016). Data mining for business analytics: Concepts, techniques, and applications with XLMiner (3rd ed.). John Wiley & Sons.
Jukic, N., Jukic, B., & Malliaris, M. (2008). Online analytical processing (OLAP) for decision
support. In F. Burstein & C. W. Holsapple (Eds.), Handbook on decision support
systems 1 (pp.259–276). Springer. https://doi.org/10.1007/978-3-540-48713-5_13
Maulik, J., & Chetna, C. (2016). Survey on privacy preservation for inference control on OLAP. International Journal of Innovative Research
TechTarget Contributor. (2023, April 5). What is a decision support system (DSS)? [Web log]. https://www.techtarget.com/searchcio/definition/decision-support-system
Power, D. J., & Sharda, R. (2023). Decision support and analytics. In Springer Handbook of Automation (pp. 1401–1410). Springer International Publishing.
AskMe. (2023, April 5). Business intelligence [Web log].
https://www.askme.co.th/article/power-bi-business-intelligence/
Yim, J., & Lee, G. (2014). Design and implementation of a user management system.
International Information Institute (Tokyo). Information, 17(10A), 5009.
Kaith, S., & Rawat, H. S. (2020). User management system. (Incomplete source – add publication details if available.)
Li, X., Huang, X., Li, C., Yu, R., & Shu, L. (2019). EdgeCare: Leveraging edge computing for
collaborative data management in mobile healthcare systems. IEEE Access, 7,
–22025
Yeshmuratova, A., & Amanbaev, N. (2023). Ensuring computer data and management system security. International Bulletin of Applied Science and Technology, 3(4), 282–287.
Eroshkin, S. Y., Kameneva, N. A., Kovkov, D., & Sukhorukov, A. (2017). Conceptual system in the modern information management. Procedia Computer Science, 103, 609–612.
Chen, J., Lv, Z., & Song, H. (2019). Design of personnel big data management system based on blockchain. Future Generation Computer Systems, 101, 1122–1129.
Polyakov, M., Khanin, I., Bilozubenko, V., & Nebaba, N. (2020). Information technologies for developing a company’s knowledge management system. Knowledge and Performance Management, 4(1), 15.
Ohliati, J., & Abbas, B. S. (2019). Measuring students’ satisfaction in using learning management system. International Journal of Emerging Technologies in Learning (iJET), 14(4), 180.
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