| dc.description.abstract | This study aims to implement the SPADE algorithm to see the associations between some components that trigger course grades and a variety of data collections. Sequential Pattern Discovery using Equivalence Class (SPADE) algorithm is one of the most effective algorithm to determine sequential pattern of data. SPADE has 3 input data to be processed to generate a sequential pattern, i.e., sid, eid, and items. The course becomes the input for sid, the student batch for eid, and value triggers of course grade become such as student grade, EPBM score, previous GPA, and employment status become the inputs for items. This research resulted in event atoms and sequential patterns amongs components that determine the course grade. It was found that 4th batch is the most frequent to outperform the previous batches to achieving better grades, and it has found a close connection between a good lecturers evaluation score and the good course grades. | en |
