Identifying key patterns of college student’s background through exploratory data analysis - Sitti Rahmah Jabir; Herdianti Darwis (Journal of Intelligent Decision Support System (IDSS), 2026)
The declining of student interest had forced universities to examine the characteristics of each student. According to higher education statistics on the number of new students, fluctuating values ​​have been found in recent years. Several research used exploratory data analysis (EDA) approach to analyze new student admissions data. EDA is offered a summary of the dataset analysis and preliminary findings. There are variables decided to be dropped because consisted high number of missing values. On the other hand, some data filled with mean and mode because the number of missing not more than 20%. The missing values in each of attribute might be cleaned using another way. The admission team in university might encourage the registrants to complete and input correct data to the system. Based on the visualization, we found that some college students applied to university from several background of area, demographic and etc. The marketing division might apply another strategy is area had small number of college which is Kalimantan. Public health, computer science and insutry technology are major that have potential to be promoted due to the job prospects.