Establishing Chatbots Utilizing the Random Forest Classification for Division of Registration and Education Statistics for the Office of Academic Promotion and Registration: Rajamangala University of Technology Tawan-ok
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The paper presents the establishing chatbots utilizing the random forest classification for division of registration and education statistics for the Office of Academic Promotion and Registration for Rajamangala University of Technology Tawan-ok. The aim is to research best practices to implement an automated response system for education statistics and registration through online platforms in university departments, assessing the effectiveness of the system as well as the user’s acceptance and extent to satisfaction regarding the information system's use. Using the Random Forest Classification and the Python programming language, it constructed a model using the learning data set, which it then applied to the development of chatbots on the Dialogflow platform. The model evaluation resulted in an Accuracy of 97.47, Precision of 92.19, Recall of 93.67, and F-Measure of 92.92, the expert's assessment of efficiency had an average of 4.26, and the user group's satisfaction evaluation had an average of 4.28. To efficiently operate the organization's informative and news release services for educators, students, and related staff.
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References
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