CLG clustering for dropout prediction using log-data clustering method

<span lang="EN-US">Implementation of data mining, machine learning, and statistical from educational department commonly known as mining. Most school systems require a teacher to teach number students at one time. Exam are regularly being use method measure student’s achievement, which is difficult understand because examination cannot be done easily. The other hand, programming classes makes source code editing UNIX commands able easily detect store automatically log-data. Hence, rather that estimating the performance those student based on this log-data, study more focused detecting them who experienced difficulty or unable take classes. We propose CLG clustering methods can predict risk dropped out using cluster for outlier detection.</span>