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This Author published in this journals
All Journal Indonesian Journal of Language and Economic Discourse Indonesian Journal of Computational Language Studies
Mohammad Anis Sumadi
Institut Agama Islam Al-Urwatul Wutsqo

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Narratives of financial inclusion: a critical discourse analysis of microfinance campaigns in rural Indonesia Mohammad Anis Sumadi
Indonesian Journal of Language and Economic Discourse Vol. 1 No. 1 (2026): Language, power, and economic narratives in Indonesia
Publisher : CV Narasi Khatulistiwa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67490/ijle.v1i1.519

Abstract

Background: Financial inclusion remains a central challenge in rural Indonesia, where microfinance campaigns are widely promoted as tools for poverty alleviation yet often carry implicit discursive and symbolic framings. Objective: The purpose of this research is to examine how empowerment is constructed in microfinance campaigns through linguistic, narrative, and visual strategies. Method: This study employed a qualitative research design integrating Critical Discourse Analysis, Narrative Analysis, and Multimodal Discourse Analysis to investigate a corpus of posters, videos, testimonials, and public statements from microfinance institutions. Results: The findings reveal that empowerment is discursively framed as a benevolent act of institutions, with slogans and public statements emphasizing collective progress while positioning citizens as dependent subjects; narrative structures predominantly follow a transformation arc, portraying hardship, intervention, and success while omitting systemic barriers; and visual-symbolic elements such as color schemes, logos, and images of women entrepreneurs reinforce institutional authority and normalize paternalistic views of empowerment. These results suggest that campaigns are effective in mobilizing participation but simultaneously constrain community agency by narrowing empowerment to institutional dependency. Implication: The implications of this study highlight the need for more participatory and reflexive approaches in financial inclusion communication that recognize rural communities as active partners rather than passive beneficiaries. Novelty: This study shows how microfinance campaigns construct empowerment through discursive, narrative, and visual strategies that mobilize participation while subtly reinforcing institutional authority and limiting community agency.
Who gets represented by Indonesian AI? measuring regional, gender, and sociolinguistic bias in large language models Mohammad Anis Sumadi
Indonesian Journal of Computational Language Studies Vol. 1 No. 2 (2026): Large language models, linguistic diversity, and responsible NLP in Indonesia
Publisher : CV Narasi Khatulistiwa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67490/ijcl.v1i2.917

Abstract

Background: Indonesia’s regional, gendered, and sociolinguistic diversity raises a critical question about whether large language models represent Indonesian identities with equal specificity, agency, and legitimacy in computational discourse. Objective: This study aims to examine how Indonesian-facing large language models generate representations of regions, gender markers, occupations, and language varieties under controlled prompt conditions. Method: Using a prompt-based audit design, this study analyses 42 prompt units divided into regional, gender-counterfactual, and sociolinguistic conditions, with coding focused on visibility, specificity, agency, competence, register alignment, semantic stability, and language shifting. Results: The findings indicate that regional representation is uneven: some regions are profiled through professional competence, while others are rendered through generic neutrality, cultural tokenisation, peripheral framing, or national homogenisation. Gendered outputs show partial professional parity, but male-coded subjects receive stronger leadership and technical authority, whereas female-coded subjects are more often associated with care, affect, and relational labour. Implication: Sociolinguistic robustness is strongest in formal Indonesian, more adaptive in colloquial Indonesian, and less stable in local-language conditions, where semantic drift, code-mixing, and defaulting to Indonesian appear. Novelty: This study contributes an intersectional audit framework that reframes Indonesian AI bias as a problem of regional visibility, gendered agency, and sociolinguistic legitimacy across culturally stratified AI systems in multilingual Indonesia today.
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