IMPLEMENTASI ALGORITMA K-MEANS DALAM CLUSTERING MINAT BACA DI PERPUSTAKAAN PADA SD NEGERI 01 KOTAPINANG

ALFANNY MARIYUANDRA, NPM 2109100006 (2025) IMPLEMENTASI ALGORITMA K-MEANS DALAM CLUSTERING MINAT BACA DI PERPUSTAKAAN PADA SD NEGERI 01 KOTAPINANG. Skripsi thesis, Universitas Labuhanbatu.

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Abstract

Minat baca siswa di SD Negeri 01 Kotapinang masih tergolong rendah, terlihat dari kurangnya kunjungan ke perpustakaan serta rendahnya partisipasi dalam kegiatan literasi. Untuk mengatasi hal ini, penelitian ini menggunakan algoritma K-Means guna menganalisis pola minat baca siswa agar dapat dirancang program literasi yang lebih tepat sasaran. Algoritma K-Means merupakan salah satu metode clustering yang efektif dalam mengelompokkan data berdasarkan kesamaan atribut tanpa memerlukan label awal, sehingga mampu memisahkan siswa ke dalam beberapa kelompok minat baca agar pihak sekolah dapat memahami pola literasi dengan lebih jelas. Penelitian ini menggunakan pendekatan kuantitatif deskriptif dengan data yang dikumpulkan melalui observasi, wawancara, dan dokumentasi di perpustakaan sekolah, yang kemudian melalui tahap preprocessing dan diolah dengan algoritma K-Means untuk menghasilkan cluster minat baca siswa. Hasil clustering menunjukkan adanya tiga kelompok siswa dengan minat baca tinggi, sedang, dan rendah berdasarkan frekuensi kunjungan, durasi membaca, serta jenis bacaan, sehingga memberikan gambaran nyata bahwa faktor kebiasaan membaca dan partisipasi literasi sangat memengaruhi distribusi minat baca. Penelitian ini membuktikan bahwa algoritma K-Means dapat digunakan secara efektif untuk mengelompokkan siswa berdasarkan tingkat minat baca di SD Negeri 01 Kotapinang, dan disarankan pihak sekolah lebih aktif mengadakan kegiatan literasi kreatif seperti lomba membaca atau klub buku agar kelompok dengan minat baca rendah dapat lebih termotivasi. Kata Kunci: Minat Baca; Perpustakaan; Clustering; K-Means; Literasi Siswa =============================== The reading interest of students at SD Negeri 01 Kotapinang is still relatively low, as evidenced by the lack of library visits and low participation in literacy activities. To address this, this study used the K-Means algorithm to analyze student reading interest patterns in order to design more targeted literacy programs. The K Means algorithm is an effective clustering method in grouping data based on attribute similarities without requiring initial labels, thus separating students into several reading interest groups so that schools can understand literacy patterns more clearly. This study used a descriptive quantitative approach with data collected through observation, interviews, and documentation in the school library, which then went through a preprocessing stage and was processed with the K-Means algorithm to produce student reading interest clusters. The clustering results showed three groups of students with high, medium, and low reading interest based on the frequency of visits, reading duration, and type of reading, thus providing a clear picture that reading habits and literacy participation factors greatly influence the distribution of reading interest. This study proves that the K-Means algorithm can be used effectively to group students based on their level of reading interest at SD Negeri 01 Kotapinang, and it is recommended that the school be more active in holding creative literacy activities such as reading competitions or book clubs so that groups with low reading interest can be more motivated. Keywords: Reading Interest; Library; Clustering; K-Means; Student Literacy

Item Type:	Thesis (Skripsi)
Uncontrolled Keywords:	Minat Baca; Perpustakaan; Clustering; K-Means; Literasi Siswa=============Reading Interest; Library; Clustering; K-Means; Student Literacy
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Divisions:	Fakultas Sains Dan Teknologi > Sistem Informasi
Depositing User:	Unnamed user with email repository@ulb.ac.id
Date Deposited:	16 Apr 2026 07:08
Last Modified:	16 Apr 2026 07:08
URI:	http://repository.ulb.ac.id/id/eprint/2124

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