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All Journal Indonesian Journal of Language and Economic Discourse Indonesian Journal of Computational Language Studies
Tifani Yuliyana
STKIP Taman Siswa Bima

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Governing through uncertainty: a corpus-assisted discourse analysis of inflation and economic recovery in Indonesian policy communication Tifani Yuliyana
Indonesian Journal of Language and Economic Discourse Vol. 1 No. 2 (2026): Language, algorithms, and economic futures in Indonesia
Publisher : CV Narasi Khatulistiwa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67490/ijle.v1i2.902

Abstract

Background: Indonesia’s post-pandemic recovery unfolded amid inflationary pressure, exchange-rate volatility, geopolitical disruption, and persistent uncertainty, making official communication central to how economic risks and policy responses were publicly understood. Objective: This study examines how Indonesian policy institutions discursively governed uncertainty while communicating inflation management and economic recovery between 2022 and 2024. Method: Using corpus-assisted discourse analysis, this study analysed 21 primary policy communications from Bank Indonesia and the Coordinating Ministry for Economic Affairs, supported by three institutional reports and four BPS statistical releases, through keyword, collocation, concordance, modality, evaluation, transitivity, legitimation, and interdiscursivity analyses. Results: Findings show that uncertainty was predominantly externalised through global pressure, geopolitical tension, imported inflation, contagion, and risk, while domestic institutions retained agency as anticipatory managers. Forward-looking modality, projections, target horizons, and calibrated caution transformed uncertain futures into temporally bounded and administratively actionable policy problems. Implication: Institutional legitimacy was constructed through maintenance, strengthening, coordination, and a functional distinction between pro-stability and pro-growth instruments, although such coherence could obscure policy trade-offs. Novelty: This study contributes an integrated account of governing uncertainty by demonstrating how lexical patterning, temporal projection, and differentiated institutional agency jointly organise economic authority, expectation management, and public legitimation in Indonesian policy communication during a period of macroeconomic adjustment and contestation
Automatic readability assessment of Indonesian educational texts using hybrid NLP approaches Tifani Yuliyana
Indonesian Journal of Computational Language Studies Vol. 1 No. 1 (2026): Data-driven approaches to Indonesian language processing
Publisher : CV Narasi Khatulistiwa Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67490/ijcl.v1i1.552

Abstract

Background: The increasing complexity of Indonesian educational texts across print and digital platforms raises concerns about mismatches with students’ reading capacities, while existing readability formulas remain largely English-centric. Objective: This study develops and evaluates an automatic readability assessment framework for Indonesian texts integrating surface metrics, linguistic features, and machine learning. Method: A stratified corpus of textbooks and digital materials was analyzed using readability indices, lexical–morphological–syntactic features, and supervised models with cross-validation. Results: Surface complexity rises across levels but shows overlap, indicating limits of traditional metrics; linguistic features such as lexical density, nominalization, and morphological complexity strongly predict readability, while hybrid ensemble models achieve the highest accuracy and lowest misclassification. Implication: These findings support the need for language-specific, multidimensional readability tools to improve text design and educational alignment in Indonesian contexts. Novelty: This study proposes a linguistically grounded hybrid NLP framework that reconceptualizes readability and enables scalable, automated evaluation of Indonesian educational texts.
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