The study of Presentation Style Perfomance of a Business Intelligence System and Chatbot for a Maintenance Support System
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Abstract
The objectives of this research are as follows: 1) to enhance the data presentation of the business intelligence system for machine maintenance support, 2) to examine the format and improve the interaction with the business intelligence system for machine maintenance support, 3) to assess user satisfaction with business intelligence, and 4) to evaluate the impact of business intelligence on users. The Waterfall model of the program development cycle is employed in the creation of business intelligence systems and conversation robots, such as chatbots. Next, the efficacy of utilization and the level of user contentment are assessed by collecting data on the requirements of those engaged in the water treatment facility at Suranaree University of Technology. Business intelligence includes technological components such as software and databases. The software was created with the Power BI software to facilitate the presentation of reports and enable interaction with the database. MySQL is utilized by the database to store machine operational data. The chatbot system was developed using Python and utilizes LINE's messaging API to deliver services and obtain system status information. In order to facilitate machine maintenance, it is necessary to establish business intelligence systems that are suitable and effective. This includes implementing a chatbot that aids in analyzing the optimal efficiency of machine operation. The study utilized a sample group consisting of students from the Faculty of Engineering (Mechanical Engineering) at Suranaree University of Technology, as well as personnel working in the water treatment plant at Suranaree University of Technology. A total of 37 individuals were included in the sample. Data collection was conducted through the administration of a questionnaire. Frequency, percentage, mean, standard deviation, and two-way analysis of variance are among the statistical measures employed in data analysis. Pair comparisons were conducted using Fisher's Least Significant Difference (LSD) if there were statistically significant differences. The findings indicate that business intelligence systems designed for machine maintenance may provide comprehensive data on water management systems, including reports on water levels, anomalies in power and water pressure, real-time monitoring through CCTV, and analysis of previous data. In a study of performance and user satisfaction, it was found that the sample group was most satisfied with the overall audio description ( = 4.32, SD = 0.589). In terms of work efficiency, the chatbot was most effective overall (
= 4.01, SD = 0.860).
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References
Aramcharoen, T. (2000). Performance measurement for a maintenance management system [Master Thesis, Chulalongkorn University]. Retrieved from https://cuir.car.chula.ac.th/handle/123456789/5957 [In Thai]
Arnott, D., & Pervan, G. (2005). A critical analysis of decision support systems research. Journal of Information Technology, 20(2), 67–87. https://doi.org/10.1057/palgrave.jit.2000035
Başal, A., Gülözer, K., & Demir, İ. (2015). Use of video and audio texts in EFL listening test. Journal of Education and Training Studies, 3(6). https://doi.org/10.11114/jets.v3i6.1001
Boranintr, V. (2009). Development of online statistical process control software for hard disk drive manufacturing [Master Thesis, Chulalongkorn University]. Retrieved from https://cuir.car.chula.ac.th/handle/123456789/15764 [In Thai]
Borup, J., Graham, C. R., & Velasquez, A. (2011). The use of asynchronous video communication to improve instructor immediacy and social presence in a blended learning environment. Blended Learning across Disciplines, 38–57. https://doi.org/10.4018/978-1-60960-479-0.ch003
Busdabong, Z. (2013). Automated incremental integration test case generation from unit test case [Mater Thesis, Suranaree University of Technology]. Retrieved from http://sutir.sut.ac.th:8080/jspui/handle/123456789/4979 [In Thai]
Cho, J., & Ghang Lee. (2019). A chatbot system for construction daily report information management. Proceedings of the 36th International Symposium on Automation and Robotics in Construction (ISARC), Banff, Canada . https://doi.org/10.22260/isarc2019/0058
Chueauan, K., Suntaranont, B., Nusen, S., Kaewmaracharoen, M. (2020). Data analysis in the construction management process using business intelligence to increase management efficiency. The 25th National Convention on Civil Engineering, Chonburi, Thailand. https://kukr.lib.ku.ac.th/kukr_es/kukr/search_detail/result/20011748 [In Thai]
Delil, S. (2017). The impact of infographic animation videos on data visualization. International Journal of Social Sciences and Education Research, 3(4), 1178–1183. https://doi.org/10.24289/ijsser.312933
Hou, C.-K. (2012). Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: An empirical study of Taiwan’s electronics industry. International Journal of Information Management, 32(6), 560–573. https://doi.org/10.1016/j.ijinfomgt.2012.03.001
Hosseini, S. S., Yamaghani, M. R., & Poorzaker Arabani, S. (2023). Multimodal modelling of human emotion using sound, image and text fusion. Signal, Image and Video Processing, 18(1), 71–79. https://doi.org/10.1007/s11760-023-02707-8
Ishibashi, T., Nakao, Y., & Sugano, Y. (2020). Investigating audio data visualization for interactive sound recognition. Proceedings of the 25th International Conference on Intelligent User Interfaces, Cagliari, Italy. https://doi.org/10.1145/3377325.3377483
Jiangsheng, X. (2011). Video monitoring system for large maintenance machinery. IEEE 2011 10th International Conference on Electronic Measurement & Instruments, Chengdu, China. https://doi.org/10.1109/icemi.2011.6037855
Magdalena, R., Ruldeviyani, Y., Sensuse, D. I., & Bernando, C. (2019). Methods to enhance the utilization of business intelligence dashboard by integration of evaluation and user testing. 2019 3rd International Conference on Informatics and Computational Sciences (ICICoS), Central Java, Indonesia. https://doi.org/10.1109/icicos48119.2019.8982481
Shivakumar (2023). Bots are hot: What the bots revolution means for IT? Retrieved from https://community.sap.com/t5/additional-blogs-by-sap/bots-are-hot-what-the-bots-revolution-means-for-it/ba-p/13217571
Moss, L. T., & Atre, S. (2003). Business intelligence roadmap (1st ed.). Pearson Education.
Nielsen, J., & Landauer, T. K. (1993). A mathematical model of the finding of usability problems. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI ’93, Amsterdam, The netherlands. https://doi.org/10.1145/169059.169166
Ockey, G. J. (2007). Construct implications of including still image or video in computer-based listening tests. Language Testing, 24(4), 517–537. https://doi.org/10.1177/0265532207080771
Phuengheng, W. & Chinnasri, W. (2017). A comparison of software development process model. APHEIT Humanities
and Social Sciences Journal, 6(2), 136-145. [In Thai]
Pi, S.-M., Li, K.-C., & Lu, C.-Y. (2018). User satisfaction and work impact of using business intelligence systems. Asian Journal of Economics, Business and Accounting, 6(4), 1–8. https://doi.org/10.9734/ajeba/2018/41072
Susena, K. C., Simanjuntak, D. M., Parwito, Fadillah, W., Yulyardo, & Girsang, A. S. (2018). Business intelligence for evaluating loan collection performance at bank. 2018 International Conference on Orange Technologies (ICOT), Nusa Dua, indonesia. https://doi.org/10.1109/icot.2018.8705829
Thaiprecha, W. (2022). Designing mobile dashboard for manufacturing using by Power BI, [Master Thesis, Silpakorn University]. Retrieved from http://ithesis-ir.su.ac.th/dspace/handle/123456789/4254 [In Thai]
Thaiprecha, W., & Puntusavase, K. (2023). Applying dashboards for manufacturing by comparing programs used
between Google data studio and Microsoft Power BI. Journal of Management Science Research, Surindra Rajabhat University, 7(3), 39-53. https://so02.tci-thaijo.org/index.php/jmsr/article/view/258426 [In Thai]
Vilarinho, S., Lopes, I., & Sousa, S. (2017). Design procedure to develop dashboards aimed at improving the performance of productive equipment and processes. Procedia Manufacturing, 11, 1634–1641. https://doi.org/10.1016/j.promfg.2017.07.314
Wagner, E. (2010). Test-takers’ interaction with an L2 video listening test. System, 38(2), 280–291. https://doi.org/10.1016/j.system.2010.01.003