DATA MINING SELEKSI SISWA BERPRESTASI UNTUK MENENTUKAN KELAS UNGGULAN MENGGUNAKAN METODE K-MEANS CLUSTERING (Studi Kasus di MTS Darul Fikri ) - Reyhan Putra Primanda; Aslan Alwi; Dyah Mustikasari (KOMPUTEK, 2021)
MTs Darul Fikri Bringin is a Tsanawiyah Madrasah located in Ponorogo. This madrasah has a good learning system to support the quality of madrasah, one of which is a superior class program. MTs Darul Fikri Bringin is always experiencing an increase in the acceptance of new student registrants every year. In determining the superior class, there are difficulties in class clustering based on students' abilities. This is due to the increasing number of registrants each year. Therefore, in this study the data mining method is applied to help cluster superior classes with student grade variables using the K-Means Clustering Algorithm and Rstudio Tools. Where the attributes used are the report card value, activeness and presence of class VII students. The K-Means Clustring Algorithm method is used to process these 12 attributes so as to produce 2 regular clusters and 1 superior cluster with the Rshiny interface in Rstudio using the R programming language. A in cluster 1 has 23 members. Classes B, C, D include regular classes which include class B in cluster 2 totaling 25 members and classes C and D in cluster 3 totaling 52 members. The application of the K-Means Clustering Algorithm and Rstudio Tools can cluster the determination and selection of superior classes at MTs Darul Fikri.