PENERAPAN ALGORITHMA APRIORI UNTUK MENEMUKAN POLA PEMILIHAN KONSENTRASI STUDI MAHASISWA - Muhammad Jamaris; Hadi Asnal; Yansyah Saputra Wijaya (AL-ULUM: JURNAL SAINS DAN TEKNOLOGI, 2020)
Exploring information or new knowledge from existing data sets is an important point of the data mining process, such as a collection of course value data that has been stored, but its potential has not been raised to find new benefits. While on the other hand there is the problem of how to find the concentration of studies that are in accordance with the competencies of the students themselves. This study was conducted to find the concentration selection pattern, based on some of the best value data from the courses that have been taken using the Apriori Algorithma, where the rules in this method will be used to find the pattern in question. Using a minimum support value of 70% produces rules with 5 item sets, namely courses in logic and algorithms, system analysis, system design, web programming and software engineering. The pattern / rule produced can be a guide for students in choosing concentration.