• PASTHAM SHRAVAN
• Dr.V.Bapuji

Data Mining, Student Network Activity There has been a shift in the management of student affairs from anecdotal, qualitative knowledge to scientific, quantitative analysis, thanks in large part to the rise and promotion of big data methods that allow teachers to understand the behaviour patterns of students in a timely and accurate manner, especially to find the groups of students that need to be focused on in a timely manner. With a total of 23.843 million Internet access records spanning 4 years, this paper uses the clustering method of data mining to analyse the campus network behaviour of 3,245 students at a specific B university. In the end, we see that there are four distinct categories of students in terms of their Internet access, and that 350 of them are heavy network users. These students' academic outcomes and general performance are impacted. Data mining was performed on student campus network behaviour in this study, which can be used as a real-world example of how data mining can be put to use in the field of student affairs management. This work provides useful information that can be used to further the professionalisation and rigour of the field.

Data -Mining, Qunatitative, Analysis, Big Data, Network Acitivity, Digital Campus

"DM (DATA MINING) & FEATURE ANALYSIS OF COLLEGE STUDENTS’ CAMPUS NETWORK BEHAVIOUR.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 6, page no.i408-i412, June-2023, Available :http://www.jetir.org/papers/JETIR2306844.pdf

"DM (DATA MINING) & FEATURE ANALYSIS OF COLLEGE STUDENTS’ CAMPUS NETWORK BEHAVIOUR.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 6, page no. ppi408-i412, June-2023, Available at : http://www.jetir.org/papers/JETIR2306844.pdf