ANDREANSYAH PANE, NPM 2109100010 (2025) KLASTERISASI MINAT BAKAT SISWA DENGAN METODE K-MEANS Di SMP NEGERI 2 KUALUH SELATAN LABUHANBATU UTARA. Skripsi thesis, Universitas Labuhanbatu.
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Abstract
Pendidikan di tingkat Sekolah Menengah Pertama memiliki peran penting dalam membentuk minat dan bakat siswa sebagai dasar penentuan jalur pendidikan maupun karier di masa depan. Namun, keragaman karakteristik siswa seringkali menyulitkan sekolah dalam memetakan potensi mereka secara efektif. Penelitian ini bertujuan untuk mengelompokkan minat dan bakat siswa SMP Negeri 2 Kualuh Selatan, Labuhanbatu Utara, menggunakan metode K-Means Clustering dengan bantuan perangkat lunak RapidMiner. Data diperoleh melalui kuesioner yang mencakup aspek akademik, seni, olahraga, dan kegiatan ekstrakurikuler lainnya. Proses penelitian meliputi tahap pengumpulan data, preprocessing, penentuan jumlah klaster optimal dengan metode Elbow, serta analisis hasil klasterisasi. Hasil penelitian menunjukkan bahwa metode K-Means berhasil membagi siswa ke dalam tiga klaster utama dengan tingkat kesamaan minat dan bakat yang tinggi di dalam kelompok dan perbedaan signifikan antar kelompok. Temuan ini memberikan landasan bagi sekolah untuk merancang kurikulum, kegiatan ekstrakurikuler, dan layanan bimbingan yang lebih terarah sesuai dengan kebutuhan siswa. Dengan demikian, penerapan metode K-Means terbukti efektif sebagai alat pendukung pengambilan keputusan dalam pengembangan potensi siswa secara lebih personal dan komprehensif. Kata Kunci: Minat dan bakat, K-Means Clustering, Data Mining, RapidMiner, Pendidikan ============================================================================================== Education at the junior high school level plays a crucial role in shaping students’ interests and talents as the foundation for future educational and career choices. However, the diversity of student characteristics often makes it difficult for schools to effectively map their potential. This study aims to cluster the interests and talents of students at SMP Negeri 2 Kualuh Selatan, Labuhanbatu Utara, using the K-Means Clustering method with the aid of RapidMiner software. Data were collected through questionnaires covering academic, artistic, sports, and extracurricular aspects. The research process included data collection, preprocessing, determining the optimal number of clusters using the Elbow method, and analyzing the clustering results. The findings show that the K-Means method successfully grouped students into three main clusters, with high intra cluster similarity and significant inter-cluster differences. These results provide a foundation for schools to design curricula, extracurricular activities, and counseling services that are more targeted and aligned with students’ needs. Therefore, the application of the K-Means method is proven to be effective as a decision-support tool for the personalized and comprehensive development of students’ potential. Keywords: Interests and talents, K-Means Clustering, Data Mining, RapidMiner, Education
| Item Type: | Thesis (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Minat dan bakat, K-Means Clustering, Data Mining, RapidMiner, Pendidikan==============Interests and talents, K-Means Clustering, Data Mining, RapidMiner, Education |
| Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software |
| Divisions: | Fakultas Sains Dan Teknologi > Sistem Informasi |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 29 Sep 2025 07:22 |
| Last Modified: | 29 Sep 2025 07:22 |
| URI: | http://repository.ulb.ac.id/id/eprint/1738 |
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