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All Journal Jurnal Teknik Informatika (JUTIF) Protasis: Jurnal Bahasa, Sastra, Budaya, dan Pengajarannya
Muhammad Kholilurrahman
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Humanities Computer Science & IT Languange, Linguistic, Communication & Media

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Artificial Intelligence in Monetary Response: The Role of Investor Sentiment in the Effectiveness of Bank Indonesia’s Interventions Dody Indra Sumantiawan; M. Zakki Abdillah; Muhammad Kholilurrahman
Jurnal Teknik Informatika (Jutif) Vol. 7 No. 2 (2026): JUTIF Volume 7, Number 2, April 2026
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2026.7.2.5184

Abstract

Exchange rate stability is a core pillar of macroeconomic resilience, especially for emerging economies like Indonesia. The effectiveness of Bank Indonesia’s (BI) monetary interventions in stabilizing the Rupiah depends not only on policy instruments but also on market perceptions and investor sentiment. This study examines the relationship between investor sentiment and the effectiveness of BI’s interventions by integrating Natural Language Processing (NLP), event study, and moderated regression analysis. The dataset spans 2023–2025 and includes daily exchange rate data, an investor sentiment index derived from financial forums and business news using VADER and TextBlob algorithms, and BI intervention records. An event study with a ±5 day window evaluates the short-term impact of interventions on exchange rate returns, while moderated regression analyzes the interaction between sentiment and interventions. Results indicate that BI interventions produce short-term exchange rate recovery, with a cumulative average abnormal return (CAAR) of 0.55% on the third day after intervention. Regression findings show that investor sentiment significantly influences Rupiah movements (p < 0.01), and the interaction between sentiment and interventions is also significant (p < 0.05), indicating greater effectiveness under positive or neutral sentiment. These findings underscore that intervention success is closely tied to market psychology. Therefore, BI should incorporate AI-driven sentiment analysis into policy design to enhance intervention effectiveness and strengthen public communication credibility. This study enriches the literature on behavioral macroeconomics and offers a data-driven framework for adaptive monetary policymaking in the digital economy.
Problematika Evaluasi Pembelajaran Bahasa Arab Berbasis Digital Nawal Sa’adah; Wilda Widya Armadani; Muhammad Kholilurrahman; Andi Nur Pratiwi; Ummul Khaeriah; Herdah Herdah
Protasis: Jurnal Bahasa, Sastra, Budaya, dan Pengajarannya Vol. 5 No. 1 (2026): Juni: Jurnal Bahasa, Sastra, Budaya, dan Pengajarannya
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/protasis.v5i1.270

Abstract

This study examines the problematics of digital-based evaluation in Arabic language learning in the context of contemporary educational transformation. The background of this research is rooted in the increasing use of digital technology in assessment practices, which raises questions regarding its effectiveness in measuring comprehensive language competence. The objective of this study is to analyze the main challenges faced in implementing digital evaluation in Arabic language learning. This research employs a qualitative approach through library research, utilizing documentation techniques to collect data from relevant scholarly sources published between 2020 and 2026. The data were analyzed using content analysis by identifying, categorizing, and interpreting recurring issues in digital assessment practices. The findings indicate that digital evaluation still faces several limitations, including the inability to measure productive language skills comprehensively, issues of validity and reliability, potential academic dishonesty, low digital literacy among users, unequal access to technology, suboptimal evaluation design, ethical concerns in technology use, and lack of alignment with the communicative nature of Arabic language learning. These findings imply that digital evaluation requires an integrative approach that combines technological innovation with pedagogical principles, emphasizing authentic and performance-based assessment. The study also highlights the importance of improving digital literacy and providing adequate infrastructure to ensure fair and effective evaluation practices.
Co-Authors Andi Nur Pratiwi Dody Indra Sumantiawan Herdah Herdah M. Zakki Abdillah Nawal Sa’adah Ummul Khaeriah Wilda Widya Armadani