Aplikasi Data Mining Untuk Klasifikasi Kesiapan Skripsi Menggunakan Algoritma Apriori - Mohammad Malik Abdul Azis; Ahmad Afif Supianto; Nanang Yudi Setiawan (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Thesis is a mandatory thing that must be done by a student to get a bachelor's degree. Based on the PSIK data from the Faculty of Computer Science, Brawijaya University, from 192 data, 96 students completed the thesis according to the specified time 95 other students did not complete the thesis according to the specified time span of 6 months. So based on these problems a system is needed that can explore knowledge - new knowledge and can help make decisions using data mining. In this study using one of the data mining tasks namely Association Rule Mining using the Apriori algorithm produces rule patterns that can be used as parameters for the prediction of thesis readiness. The collected data supports 540 academic program data records of 2013 - 2014 Information System study students and 192 FILKOM APPS data records that contain progress data for student thesis in 2018, then pre-processing to use the usage pattern using Apriori with WEKA tools. The results of testing the system using a black box show valid results so that it can be concluded that the system is made according to requirements. Then to test usability obtained a value of 67.5 which belongs to the predicate D for Scale Scale and Marginal Height for the Acceptance Range.