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All Journal Jurnal Informatika dan Rekayasa Perangkat Lunak Paradigma Jurnal Informatika: Jurnal Pengembangan IT
Pamput, Jessicha Putrianingsih
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Computer Science & IT

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Journal : Paradigma

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K-Means++ and TF-IDF for Grouping Library Books by Topic Pamput, Jessicha Putrianingsih; Muthmainnah, Aindri Rizky; Risal, Andi Akram Nur; Surianto, Dewi Fatmarani
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 2 (2025): September 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i2.8272

Abstract

The grouping of library materials in the Department of Informatics and Computer Engineering (JTIK) at Universitas Negeri Makassar (UNM) is still conducted using a conventional system that relies on predefined categories and librarian intuition. This approach often leads to inconsistencies in book categorization, making it difficult for users to find relevant references efficiently. To address this issue, this research applies the K-Means++ clustering method, which optimizes centroid initialization for more accurate cluster formation. Books are grouped based on the TF-IDF weighting matrix, resulting in six distinct clusters characterized by unique centroid values. Analysis of the top 10 words per cluster highlights dominant topics within each group. The clustering quality was evaluated using the Silhouette Coefficient, with the highest value of 0.04299, indicating a well-separated cluster structure. These findings demonstrate that K-Means++ effectively organizes books based on word similarity, enhancing library material management and improving information retrieval in the JTIK library.
Co-Authors Adiba, Fhatiah Andi Akram Nur Risal Dewi Fatmarani Surianto Muthmainnah, Aindri Rizky Nasrullah, Asmaul Husnah NUR FADILAH