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APLIKASI DATA MINING UNTUK MENGANALISIS ATURAN ASOSIASI TRACER STUDY DI IBI-KOSGORO1957
Abstract
Graduates as the end product of educational institutions are the quality objective and benchmark for the success of educational institutions. One strategy for obtaining feedback from graduates is using Tracer Study. This study aims to find and then analyze associative patterns can be found in the IBI-Kosgoro 1957 tracer study data. The search for association rules is carried out using the apriori algorithm. These patterns will be used to evaluate the characteristics of IBI-Kosgoro 1957 graduate students. Implementation of data mining is done using the Python programming language and executed using Google Colabs. The dominant characteristics of the IBI Kosgoro 1957 graduates are there are more non-entrepreneurial office workers, less active in organizations, moderate GPA scores, but can speak at least one foreign language and the most language is English. There are more who work not according to their educational background than work according to their scientific field, the proportion is almost the same. The GPA value itself does not affect success in getting a job that earns above UMP. Even so, 30% of them earn above UMP. With a minimum support of 10% and confidence above 50%, graduates will work according to their field of knowledge and earn an income above the UMP if they are bilingual, not actively organized and quickly looking for work.
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DOI: https://doi.org/10.34001/jdpt.v14i1.3909
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