Data Mining Modeling Feasibility Patterns of Graduates Ability With Stakeholder Needs Using Apriori Algorithm


  • Titin Winarti Universitas Semarang
  • Henny Indriyawati Universitas Semarang



Data Mining, Apriori Algorithm, Modeling, Patterns


This The speed of information, the accuracy of data, the ease of information services, and accountability are very important reasons for the implementation of the system. Semarang University (USM) is a private university in Semarang that has the most 2 students in Central Java. Based on the 2019 USM tracer data showing horizontal alignment, namely how close the relationship between the field of study and alumni work is, it appears that there is still a discrepancy in the ability of graduates with stakeholders.  The Apriori algorithm is the best-known algorithm for finding high-frequency patterns  Rules that state associations between attributes are often called affinity analysis or market basket analysis. The use of the Apriori Algorithm in data mining calculations using data from the Semarang University tracer that the limit of the minimum support is 50% and the minimum confidence is 100% so that it forms 4 rules. From the four rules produced that modeling using the Apriori Algorithm can produce several rule formations so that it can provide an evaluation to the University for compiling steps, this can be seen because the resulting rules are different because each graduate relationship with the desired desires and different styles.



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