Predicting the Assessment Course Performance of Criminology Students Using Data Mining

Living in this changing era where things constantly change overtime, transitioning means not a big thing. Obviously, nowadays even learning often takes place outside of traditional educational settings. This study aims to determine the performance of criminology students in the assessment course. The research covers the analysis of the performance of Criminology students of Legacy College of Compostela in the Assessment Course with six (6) subject areas. The data were taken from the College of Criminal Justice Education (CCJE) students' evaluation, Multiple Linear Regression was employed to predict the students' performance in the assessment course. The data mining study results were acquired using IBM SPSS as the Modeler to transform the data and extract relevant information, which was then used for the conclusion. Based on the results, it can be concluded that the subjects of Crime Detection and Investigation and Law Enforcement Administration significantly influence the outcome of the students' assessments. Therefore, to concentrate on reviewing other areas with students, such as correlational administration, criminalistics, criminal law and procedure, and criminal sociology, might be useful in improving students' performance.