Penerapan Data Mining Untuk Rekomendasi Bidang Studi Menggunakan Algoritma K-Medoids Pada SMA N 9 Kota Jambi - Gustirani, Amalinda; Jasmir; Fachruddin (LPPM Universitas Dinamika Bangsa, 2024)
Education is a process that develops a person in terms of mindset, attitude, character, language, and role in society. This study aims to apply data mining in recommending fields of study in universities using the K-Medoids algorithm. From the research conducted, researchers recommend 8 clusters, which is calculated manually and using RapidMiner. The results obtained manually in cluster 1 showed that there were 11 students who entered the Agriculture and Animal Husbandry Sector, cluster 2 had 65 students entering the Sports Sector, cluster 3 had 29 students entering the Health Sector, cluster 4 has 7 students entering the Science and Technology field, cluster 5 has 30 students entering the Education Sector, cluster 6 has 39 students entering the Economics field, cluster 7 there are 17 students entering the Religion Field, cluster 8 there are 27 students entering the Arts Field. Meanwhile using RapidMiner in cluster 1 there were 32 students, cluster 2 has 36 students, cluster 3 has 26 students, cluster 4 has 17 students, cluster 5 has 30 students, cluster 6 has 31 students, cluster 7 has 39 students, cluster 8 has 14 students. Hoped the results of applying the K-Medoidsss algorithm can help students determine their field of study in college.