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All Journal TRANSIENT: Jurnal Ilmiah Teknik Elektro Computer Science and Information Technologies
Dela Nurlaila
Jurusan Teknik Elektro, Universitas Diponegoro Semarang Jl. Prof. Sudharto, SH, Kampus UNDIP Tembalang, Semarang 50275, Indonesia
Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : Computer Science and Information Technologies

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Optimizing diplomatic indexing: full-parameter vs low-rank adaptation for multi-label classification of diplomatic cables Nurlaila, Dela; Girsang, Abba Suganda
Computer Science and Information Technologies Vol 6, No 3: November 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i3.p274-282

Abstract

Accurate classification of diplomatic cables is crucial for Mission’s evaluation and policy formulation. However, these documents often cover multiple topics, hence a multi-label classification approach is necessary. This research explores the application of pre-trained language models (CahyaBERT, IndoBERT, and MBERT) for multi-label classification of diplomatic cable executive summaries, which align with the diplomatic representation index. The study compares full-parameter fine-tuning and low-rank adaptation (LoRA) techniques using cables from 2022-2023. Results demonstrate that Indonesian-specific models, particularly the IndoBERT, outperform multilingual models in classification accuracy. While LoRA showed slightly lower performance than full fine-tuning, it significantly reduced GPU memory usage by 48% and training time by 69.7%. These findings highlight LoRA’s potential for resource-constrained diplomatic institutions, advancing natural language processing in diplomacy and offering pathways for efficient, real-time multi-label classification to enhance diplomatic mission evaluation.
Co-Authors Abba Suganda Girsang, Abba Suganda Maman Somantri R. Rizal Isnanto