IMPLEMENTASI DEEP LEARNING MENGGUNAKAN HYBRID SENTENCE-TRANSFORMERS DAN K-MEANS UNTUK PERBANDINGAN JURNAL
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Abstract
This study addresses the challenge of identifying semantic relatedness between scientific journal articles by developing a classification system based on deep learning. The system applies an unsupervised learning approach using the Sentence-Transformers model and K-Means clustering to generate semantic similarity scores and categorical labels. Abstracts from journal PDFs are extracted and processed to determine similarity levels across four predefined categories. The optimal number of clusters was determined using Elbow Method, Silhouette Score, and Davies-Bouldin Index, resulting in k = 4. The system is implemented as a web-based application that allows users to upload two PDF files, compare them semantically, and receive both a similarity score and an AI-generated narrative explanation. Functional testing showed that all core features performed as expected. This system significantly reduces the time required to assess relatedness between journal articles, offering an efficient tool for academic research navigation.
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How to Cite
Muhammad Asygar Faeruddin, Muhammad Faisal, Rizki Yusliana Bakti, Muhammad Syafaat, Muhyiddin AM Hayat, Andi Makbul Syamsuri, & Andi Lukman Anas. (2025). IMPLEMENTASI DEEP LEARNING MENGGUNAKAN HYBRID SENTENCE-TRANSFORMERS DAN K-MEANS UNTUK PERBANDINGAN JURNAL. Jurnal Informatika Progres, 17(2), 23-35. Retrieved from https://jurnal.stmikprofesional.ac.id/index.php/Progress/article/view/431
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[4] H. T. A. Simanjuntak, P. E. P. Silaban, J. K. S. Manurung, and V. H. Sormin, “Klasterisasi Berita Bahasa Indonesia Dengan Menggunakan K-Means Dan Word Embedding,” Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 10, no. 3, pp. 641–652, 2023. doi:10.25126/jtiik.20231026468.
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[6] A. Subakti, H. Murfi, and N. Hariadi, “The performance of BERT as data representation of text clustering,” Journal of Big Data, vol. 9, no. 1, 2022. doi:10.1186/s40537-022-00564-9.
[7] Y. Ortakci, “Revolutionary text clustering: Investigating transfer learning capacity of SBERT models through pooling techniques,” Engineering Science and Technology, an International Journal, vol. 55, p. 101730, 2024. doi:10.1016/j.jestch.2024.101730.
[8] M. H. Weng, S. Wu, and M. Dyer, “Identification and Visualization of Key Topics in Scientific Publications with Transformer-Based Language Models and Document Clustering Methods,” Applied Sciences, vol. 12, no. 21, 2022. doi:10.3390/app122111220.
[9] C. Y. Sy, L. L. Maceda, and M. B. Abisado, “AI-driven analysis: optimizing tertiary education policy through machine learning insights,” International Journal of Advances in Intelligent Informatics, vol. 10, no. 2, pp. 296–316, 2024. doi:10.26555/ijain.v10i2.1525.
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[11] Octavian Ery Pamungkas et al., “Classification of Rupiah to Help Blind with The Convolutional Neural Network Method,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 6, no. 2, pp. 259–268, 2022. doi:10.29207/resti.v6i2.3852.
[12] Irbah Salsabila and Yuliant Sibaroni, “Multi Aspect Sentiment of Beauty Product Reviews using SVM and Semantic Similarity,” Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 5, no. 3, pp. 520–526, 2021. doi:10.29207/resti.v5i3.3078.
[13] S. Afriyani, S. Surono, and M. I. Solihin, “Chi-Square Feature Selection with Pseudo-Labelling in Natural Language Processing,” vol. 8, no. 3, pp. 896–909, 2024.
[14] Z. Zainuddin and A. A. N. Risal, “Balanced clustering for student admission school zoning by parameter tuning of constrained k-means,” IAES International Journal of Artificial Intelligence, vol. 13, no. 2, pp. 2299–2311, 2024. doi:10.11591/ijai.v13.i2.pp2301-2313.
[15] E. M. Hambi and F. Benabbou, “A deep learning based technique for plagiarism detection: A comparative study,” IAES International Journal of Artificial Intelligence, vol. 9, no. 1, pp. 81–90, 2020. doi:10.11591/ijai.v9.i1.pp81-90.
[16] R. Annisa, D. Rosiyadi, and D. Riana, “Improved point center algorithm for k-means clustering to increase software defect prediction,” International Journal of Advances in Intelligent Informatics, vol. 6, no. 3, pp. 328–339, 2020. doi:10.26555/ijain.v6i3.484.