Pengelompokkan Mahasiswa Akademik Keperwatan Berdasarkan Asal Sekolah dan Nilai Akademik Menggunakan Metode Clustering K-Means


  • Lisna Zahrotun * Mail Universitas Ahmad Dahlan, Yogyakarta, Indonesia
  • Yunus Fajri Universitas Ahmad Dahlan, Yogyakarta, Indonesia
  • Anna Hendri Soleliza Jones Universitas Ahmad Dahlan, Yogyakarta, Indonesia
  • Eni Purwaningsih Universitas Ahmad Dahlan, Yogyakarta, Indonesia
  • (*) Corresponding Author
Keywords: Data Mining; Clustering; K-Means

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

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Article History
Submitted: 2021-12-21
Published: 2021-12-31
Abstract View: 139 times
PDF Download: 113 times
How to Cite
Zahrotun, L., Fajri, Y., Jones, A. H. S., & Purwaningsih, E. (2021). Pengelompokkan Mahasiswa Akademik Keperwatan Berdasarkan Asal Sekolah dan Nilai Akademik Menggunakan Metode Clustering K-Means. Building of Informatics, Technology and Science (BITS), 3(3), 369-374. https://doi.org/10.47065/bits.v3i3.1110
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