Abstract
Nursing Academic of Karya Bakti Husada (AKPER KBH) Bantul is one of the academics that opened the 2000 department. Based on an interview with the Director of AKPER KBH, the registration requirements to become a student of the Academy are currently graduates from all majors and all high schools. AKPER KBH has not analyzed student data whether there is a relationship between high school history and passing grades of GPA as an evaluation material in the learning process, although at this time with the variation of new students causing difficulty in learning difficult compared to before, while GPA achievement is very important in finding job after graduation. The purpose of this study is to classify academic data of AKPER students based on data on school origin, GPA scores, and Medical Surgical Nursing II (KMB II), Mental Nursing II (Kep Jiwa II), Child Nursing II (Kep Anak II), Maternity Nursing II (Kep Maternitas II), and Medical Surgical Nursing ( KMB V). The stages in this study include data collection, data search, data selection, data transformation, data grouping using the K-Means method and knowledge representation, the test used in this study is the purity test. From the experiments conducted, the accuracy value is 0.924 with the number of clusters 3
Highlights
Pendidikan tenaga medis di Indonesia merupakan salah satu pendidikan yang memiliki banyak peminat, diantaranya jurusan keperawatan
the registration requirements to become a student of the Academy are
analyzed student data whether there is a relationship between high school history
Summary
Pendidikan tenaga medis di Indonesia merupakan salah satu pendidikan yang memiliki banyak peminat, diantaranya jurusan keperawatan. Berdasarkan wawancara dengan Direktur AKPER KBH syarat pendaftaran menjadi mahasiswa keperawatan saat ini adalah siswa lulusan dari semua jurusan dan semua sekolah menengah. Penelitian tentang pengelompokkan data riwayat mahasiswa sebelum kuliah dan masa studi juga pernah dilakukan sebelumnya dengan menggunakan metode K-Medoids [6] dan Aglomerafit Hierarchical Clustering (AHC) [7]. Dengan adanya teknik-teknik data mining dalam penggalian data, maka dalam penelitian ini akan dilakukan analisis data mahasiswa AKPER KBH dengan melakukan pengelompokkan data akademik mahasiswa dan mencari pola asosiasi antara variable data sebelum kuliah dan nilai IPK. Hasil analisis ini siharapkan mampu memberikan rekomendasi terhadap syarat penerimaan mahasiswa baru pada AKPER KBH di tahun-tahun berikutnya
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