Penentuan Pola Asosiatif Data Tracer Study Universitas Semarang dengan Algoritma Hash Based
DOI:
https://doi.org/10.24246/aiti.v20i2.150-166Keywords:
associative, apriori, data mining, hash based, tracer studyAbstract
Data from the tracer study of Semarang University has not yet been processed into an associative pattern. It can be utilized by the campus to obtain feedback on the evaluation of the success of the teaching and learning process that has been implemented. This study uses a data mining method with a hash-based algorithm to find associative patterns in the tracer study data. The process of forming an associative pattern uses the stages of Knowledge Discovery in Database, which include cleaning data, integration, data transformation, data mining, pattern evaluation, and knowledge representation. With minimum support of 50% and 75% confidence, the study results obtained tracer study data patterns of three associative patterns. The pattern is intended to contribute to curriculum development and supporting facilities in the learning process.
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