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All Journal Journal of Citizenship Journal of Artificial Intelligence and Legal Technology
Dybio Asih
Universitas Wirahusada Medan
Social Sciences

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Komunikasi Visual dalam Sistem Informasi Lingkungan Digital untuk Meningkatkan Kesadaran Ekologi di Kalangan Masyarakat Medan Sunggal Dybio Asih; Dede Tarigan; Jasael Simanullang
Journal of Citizenship Volume 5 Issue 1, 2026
Publisher : HK Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37950/joc.v5i1.655

Abstract

This study aims to understand how visual communication in digital environmental information systems contributes to the development of ecological awareness among the Medan Sunggal community. This study focuses on the phenomenon of communication of meaning construction through visual elements in digital platforms used to disseminate environmental information. A qualitative research design was used by conducting in-depth interviews with community members and analyzing the visual content of digital environmental information systems, including infographics, symbols, color usage, and visual narratives. Data were analyzed using thematic analysis to identify patterns in user interpretation, understanding, and perceived relevance of visual communication. The results show that visual elements that reflect local context, simplicity, and symbolic clarity play an important role in enhancing message comprehension and fostering ecological awareness. Digital environmental information systems function not only as information providers but also as communicative spaces where visual design mediates public understanding of environmental issues. This study is limited to a specific local environment and does not measure long-term behavioral outcomes, suggesting that future research should examine the impact of behavior or comparative cultural contexts. The originality of this study lies in its focus on local visual communication practices in digital environmental information systems, which offers valuable insights into applied communication strategies that integrate cultural context and visual meaning-making to support environmental awareness initiatives.
An Experimental Evaluation of Machine Learning Models for Judicial Decision Prediction Using Indonesian Court Decisions Dybio Asih
Journal of Artificial Intelligence and Legal Technology Vol. 2 No. 1 (2026): February 2026
Publisher : Sah Publisher

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Abstract

Judicial outcome analysis has attracted growing attention within legal artificial intelligence research; however, empirical studies focusing on Indonesian court decisions remain limited. This study presents an experimental evaluation of traditional machine learning and deep learning models for judicial outcome classification using Indonesian legal texts.The experiments were conducted on a curated dataset of 4,872 court decisions obtained from the official Direktori Putusan Mahkamah Agung Republik Indonesia (2018–2023). To prevent outcome leakage, all explicit ruling sections were removed prior to model training, and only the legal reasoning segments were used as input. Several models, including Logistic Regression, Support Vector Machine, Gradient Boosting, BiLSTM, and IndoBERT, were evaluated under identical experimental settings. The results show that ensemble-based methods, particularly Gradient Boosting, achieve strong and stable performance, while deep learning models demonstrate competitive but not consistently superior results under document length constraints. Error analysis indicates that misclassifications frequently arise from implicit judicial reasoning and outcome ambiguity. This study provides an empirical benchmark for judicial outcome classification in Indonesian courts and highlights methodological limitations related to document length, labeling granularity, and reproducibility in legal NLP research.
Co-Authors Dede Tarigan Jasael Simanullang