Titi Farhanah
UIN Syarif Hidayatullah, Jakarta, Indonesia

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Accuracy of K-Nearest Neighbors Algorithm Classification For Archiving Research Publications Muhamad Nur Gunawan; Titi Farhanah; Siti Ummi Masruroh; Ahmad Mukhlis Jundulloh; Nafdik Zaydan Raushanfikar; Rona Nisa Sofia Amriza
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3915

Abstract

The Archives and Research Publication Information System plays an important role in managing academic research and scientific publications efficiently. With the increasing volume of research and publications carried out each year by university researchers, the Research Archives and Publications Information System is essential for organizing and processing these materials. However, managing large amounts of data poses challenges, including the need to accurately classify a researcher's field of study. To overcome these challenges, this research focuses on implementing the K-Nearest Neighbors classification algorithm in the Archives and Research Publications Information System application. This research aims to improve the accuracy of classification systems and facilitate better decision-making in the management of academic research. This research method is systematic involving data acquisition, pre-processing, algorithm implementation, and evaluation. The results of this research show that integrating Chi-Square feature selection significantly improves K-Nearest Neighbors performance, achieving 86% precision, 84.3% recall, 89.2% F1 Score, and 93.3% accuracy. This research contributes to increasing the efficiency of the Archives and Research Publication Information System in managing research and academic publications.