| People |
Contact |
| E-ISSN | : 3163-7884 | |
| Editor-in-chief | : Achmad Fawaid 57214837323 |
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| Accreditation No. | : 00/KPT/00.00/202x | |
| DOI | : Prefix by |
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| Frequency | : 4 issues per year (quarterly) | |
| Focus & Scope | : Linguistics and computational approaches | |
| Citation & Indexing | : Garuda, Google Scholar, Issuu, BRIN, Copernicus | |
| Author Guidelines | ||
| Submit Paper Now! |
About the Journal
Indonesian Journal of Computational Language Studies is a double blind peer-reviewed scholarly journal that publishes original research articles and critical studies at the intersection of language, computation, and data-driven methodologies. This journal is published quarterly as a platform for the dissemination of theoretical, empirical, and interdisciplinary findings that explore how computational approaches contribute to the analysis, modeling, and understanding of linguistic phenomena. It addresses a broad range of topics, including but not limited to computational linguistics, natural language processing, corpus linguistics, language modeling, machine learning for language analysis, discourse and text mining, digital humanities, language technologies, and computational approaches to language use across social, cultural, and digital contexts.
ASJC Code: 3310 – Linguistics and Language; 1702 – Artificial Intelligence; 1710 – Computer Science Applications
By publishing in Indonesian Journal of Computational Language Studies, authors become part of an international scholarly community dedicated to advancing theoretical, applied, and interdisciplinary perspectives on language through computational and technological innovation. This journal welcomes contributions from established academics, early-career researchers, and doctoral scholars who seek a reputable and forward-looking venue for impactful studies that integrate linguistic theory, computational methods, and data-driven analysis in contemporary language research.
Current Issue
Articles
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Beyond translated benchmarks: a culturally grounded evaluation of large language models for Indonesian language understanding
Abstract View: 44,
PDF Download: 22
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When safety fails in local languages: evaluating culturally sensitive responses of large language models in multilingual Indonesia
Abstract View: 36,
PDF Download: 18
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Hallucinating the archipelago: detecting factual and cultural errors in retrieval-augmented generation for Indonesian knowledge
Abstract View: 37,
PDF Download: 27
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Small models, many languages: parameter-efficient adaptation of multilingual language models for low-resource Indonesian languages
Abstract View: 38,
PDF Download: 18
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Who gets represented by Indonesian AI? measuring regional, gender, and sociolinguistic bias in large language models
Abstract View: 35,
PDF Download: 27








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