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Journal of International Conference Proceedings
Published by AIBPM Publisher
ISSN : 26220989     EISSN : 2621993X     DOI : https://doi.org/10.32535/
Core Subject : Humanities, Science, Education, Engineering,
Humanities Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media
JICP is proceedings series that aims to publish proceedings from conferences, in the fields of economics, business, and management research. All proceedings in this website are open access, which means the published articles are permanently free to read, download, copy, and distribute. The online publication of each proceedings is sponsored by the conference organizers and hence no additional publication fees are required. JICP helps the Conference Organisers to increase impact of their conference with Online Abstract Book and also fullpaper book and Indexed Publication of the abstracts. JICP has vision which is to publish scholarly empirical and theoretical research articles, offering the authors and readers alike an academic rigor as well as professional development.
Arjuna Subject : Umum - Umum
Articles 1,586 Documents
 155   156   157   158   159 
The Role of AI Governance and Digital Accountability in Promoting Inclusive Economic Development in Central Kalimantan Pratiwi Subianto; Abdul Halim; Tiur Roida Simbolon; Kasi Eselonirmala Waruwu
Journal of International Conference Proceedings Vol 9, No 1 (2026): 2026 Dili ICPM Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v9i1.4686

Abstract

Artificial Intelligence (AI) has emerged as a key driver of global economic transformation, offering opportunities for productivity growth, public service efficiency, and regional innovation. However, AI also poses risks of socioeconomic inequality, algorithmic bias, digital exclusion, and weak accountability, challenges particularly pronounced in developing regions like Central Kalimantan. This study analyzes the role of AI Governance and accountability in driving inclusive economic development and formulates a Digital Accountability Framework for Central Kalimantan using a Systematic Literature Review (SLR) with a PRISMA approach. Findings reveal that AI can support inclusive growth through agriculture productivity, forest fire monitoring, targeted public services, and SME strengthening. Without ethical governance, however, AI risks deepening inequality, marginalizing indigenous communities, and creating dependency on nontransparent systems. Therefore, AI Governance must function as institutional development infrastructure. The proposed framework encompasses transparency, fairness, human oversight, data governance, grievance mechanisms, and multistakeholder involvement for inclusive, adaptive, and sustainable development in Central Kalimantan.
Study of Loss Aversion Theory Based on Connected Papers AI Rahmah Dianti Putri; Mahatma Kufepaksi; Prakarsa Panjinegara
Journal of International Conference Proceedings Vol 8, No 7 (2025): 2025 Bali ICPM Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v8i7.4723

Abstract

This study aims to analyze loss aversion behavioral bias in the capital market by utilizing artificial intelligence technology. The method used in this study is a literature review, and the literature sources were obtained using Connected Papers AI by entering the keyword “Loss Aversion.” Next, several recommended article titles related to the keyword will appear. In this study, the author chose the article title “Behavioral Risk Profiling: Measuring Loss Aversion of Individual Investors” as the main article. Then, Connected Papers AI created a visualization graph of articles that have a strong relationship with the reference article in terms of co-citation and bibliography merging. The author used the articles based on the visualization graph to create a literature review. From the visualization results, it can be seen that research on loss aversion is rooted in decision-making theory under risk, based on the prospect theory framework. aversion in time frame or social conditions.
Visual Storytelling and Micro-Influencer Collaboration: Driving Purchase Intent in Fashion E-commerce Heru Tri Sutiono; Tugiyo Tugiyo; Sri Harjanti; Fitriana Ayu Eka Safina; Fajar Haryo Nimpuno
Journal of International Conference Proceedings Vol 7, No 4 (2024): 2024 Wimaya Yogyakarta Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v7i4.3739

Abstract

This study aims to investigate the influence of visual storytelling and micro-influencers on fashion purchase intention among Generation Z in Indonesia. The research employed a quantitative approach, utilizing a self-administered online questionnaire. The findings of the study reveal that both visual storytelling and consumer engagement significantly impact purchase intention. Visual storytelling, particularly when engaging and relevant, positively influences consumer perception and, subsequently, purchase intent. However, consumer engagement emerges as a stronger predictor, emphasizing the importance of fostering interaction and community around the brand. While micro-influencers were expected to play a significant role, the results indicate a limited impact on purchase intention. This suggests that while micro-influencers can contribute to brand awareness and credibility, their influence may be less pronounced compared to other factors such as visual storytelling and consumer engagement. The study concludes by highlighting the importance of creating visually appealing and engaging content that fosters active consumer participation.
Do Sectoral Stock Indices Predict Sectoral Economic Growth? :A Systematic Literature Review of Evidence for Mixed Frequency Forecasting in Emerging Markets Muhammad Ardi Ardi; Fahrudin Zain Olilingo; RAFLIN HINELO; ROBIYATI PODUNGGE
Journal of International Conference Proceedings Vol 9, No 1 (2026): 2026 Dili ICPM Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v9i1.4713

Abstract

This study systematically reviews the literature on the ability of sectoral stock indices to predict sectoral economic growth, particularly using mixed-frequency forecasting approaches in emerging markets. The issue is important because stock markets operate at high frequencies (daily or weekly), while sectoral economic indicators—such as industrial output, sectoral GDP, and production indices—are typically available at lower frequencies (monthly, quarterly, or annually). This mismatch creates both methodological challenges and analytical opportunities in integrating financial and real-sector data. Using a systematic literature review, the study synthesizes theories of market efficiency, the relationship between finance and economic growth, and the Mixed Data Sampling (MIDAS) approach. The literature indicates that stock prices may contain forward-looking information related to profit expectations, sectoral demand, financing conditions, and investor sentiment. However, empirical evidence at the sectoral level in emerging markets remains mixed due to differences in market structures, macroeconomic volatility, uneven liquidity, and data limitations.The study concludes that integrating sectoral stock indices with economic indicators through mixed-frequency models offers valuable contributions to macro-financial forecasting, although further sector-specific and country-specific empirical research is still needed..  Keywords: sectoral stock indices; economic growth, mixed-frequency, MIDAS; emerging markets; forecasting; macro-financial.
INTEGRATING ARTIFICIAL INTELLIGENCE AND DIGITAL TECHNOLOGY IN CONTEMPORARY PROJECT MANAGEMENT: Evolution of Data-Based Decision-Making Systems Romualdus Turu Putra Maro Djanggo; Adi Maulana Rachman; Zahania Suhendi Zahra
Journal of International Conference Proceedings Vol 9, No 2 (2026): 2026 Vietnam ICPM Proceeding
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Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v9i3.4765

Abstract

ABSTRACTThis study examines the integration of artificial intelligence (AI) and digital technology in contemporary project management practices, focusing on the evolution of data-based decision-making systems. The rapid digital transformation has shifted project management paradigms from traditional approaches toward more adaptive and predictive data-driven models. This article employs a systematic literature review method, analyzing 45 international journal articles published between 2015–2024 from Scopus, Web of Science, and Google Scholar databases. The findings reveal that AI implementation in project management significantly improves cost and schedule estimation accuracy by up to 34%, reduces project delay risk by 28%, and enhances resource allocation efficiency by 41%. Machine learning and predictive analytics prove to be the most critical components in supporting more accurate and real-time decision-making. Nevertheless, the adoption of these technologies still faces challenges including limited digital infrastructure, organizational resistance, and human resource competency gaps. This research contributes a conceptual framework for AI integration in the project lifecycle that can serve as a reference for practitioners and academics. Keywords: Artificial Intelligence (AI), Project Management, Digital Transformation, Data-Driven Decision Making, Machine Learning, Predictive Analytics.
AI-Enabled Digital Twins for Sustainable Manufacturing: A Systematic Review of Technological Functions, Sustainability Outcomes, and Managerial Implications Jacobus Rico Kuntag; Simon Siamsa; Mega Suteki; Alfarizi Alfarizi
Journal of International Conference Proceedings Vol 9, No 2 (2026): 2026 Vietnam ICPM Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v9i3.4757

Abstract

Sustainable manufacturing increasingly depends on data-driven technologies to improve productivity, cost efficiency, quality, and sustainability performance. This study reviews literature on AI-enabled digital twins in sustainable manufacturing, focusing on research trends, technological functions, sustainability outcomes, managerial implications, barriers, and future directions. Using a PRISMA-based systematic literature review of Web of Science and Scopus records, the study synthesizes 88 publications: 66 full-text studies for critical synthesis and 22 abstract-based records for descriptive mapping. Analysis combined descriptive, thematic, and integrative synthesis with framework-based coding. The findings indicate that real-time monitoring, simulation, prediction/prognostics, and optimization are the most established functions, whereas control, decision support, and autonomous adjustment remain emerging. Reported outcomes concentrate on energy and resource efficiency, waste and emission reduction, quality, downtime, and operational efficiency. The study highlights governance as a core implementation condition and calls for stronger empirical validation, standardized metrics, and robust data-model governance.
Individual Taxpayer Perceptions of the Implementation of the Digital Tax Administration System through (Coretax) in Supporting Tax Compliance: A Case Study in Merauke Regency, Indonesia Semuel Batlajery; Mensy Otelyo Kastanya; Kaila Isabela Humaero
Journal of International Conference Proceedings Vol 9, No 2 (2026): 2026 Vietnam ICPM Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v9i3.4769

Abstract

This study aims to analyze individual taxpayers' perceptions regarding the implementation of Coretax. This study uses a descriptive qualitative research approach. The informants in this study were 10 individual taxpayers. The sampling technique used propositional sampling with the criteria being individual taxpayers who have a Taxpayer Identification Number (NPWP) and individual taxpayers who use the Coretax application . Data collection techniques used interviews, observation, and documentation. Data analysis used data reduction, data presentation, and conclusion drawing techniques . The results of the study indicate that individual taxpayers have a positive perception of the implementation of Coretax, this system is able to provide easy access to tax services can increase taxpayer awareness, improve administrative efficiency, and is able to assist taxpayers in fulfilling their tax obligations. In addition, Coretax is also considered to support increased taxpayer compliance through ease of reporting and access to more integrated tax information. However, based on the results of the study there are obstacles including a lack of understanding of the new system users, technical disruptions that often still occur during use, difficulty understanding features, and lack of socialization. Overall, the implementation of Coretax makes a positive contribution in supporting individual taxpayer compliance in Merauke RegencyKeywords: Coretax;taxpayer perception;tax compliance;tax digitalization; individual taxpayers   
The Effect of Supply Chain Integration, Management Commitment, and Sustainable Supply Chain Practices on the Performance of Craft MSMEs in Bantul Regency Luki Antoro; Titik Kusmantini; Nilmawati Nilmawati
Journal of International Conference Proceedings Vol 8, No 6 (2025): 2025 WIMAYA Yogyakarta Proceeding
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Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v8i6.4784

Abstract

This study examines the effects of Supply Chain Integration (SCI) and Management Commitment (MC) on the performance of handicraft MSMEs in Bantul Regency. Drawing on the Natural Resource-Based View and Dynamic Capabilities Theory, the study investigates the role of Sustainable Supply Chain Practices (SSCP) as a mediating variable and Supply Chain Challenges (SCC) as a moderating variable. A quantitative approach was employed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) based on survey data collected from 100 owners and managers of verified handicraft MSMEs in Bantul Regency, Indonesia. The results indicate that Supply Chain Integration and Management Commitment have significant positive effects on both Sustainable Supply Chain Practices and MSME performance. Sustainable Supply Chain Practices also have a significant positive effect on MSME performance. However, SSCP does not significantly mediate the relationships between SCI, MC, and MSME performance. Furthermore, Supply Chain Challenges significantly moderate the relationship between SSCP and MSME performance
Artificial Intelligence Based Financial Digital Twin Framework for Credit Risk Monitoring in Banking Systems Ni Luh Putu Nita Yulianti; Yumiad Fernando Richard; Apolinaris S Awotkay; Kania Miftahul Jannah
Journal of International Conference Proceedings Vol 9, No 2 (2026): 2026 Vietnam ICPM Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v9i3.4758

Abstract

Artificial Intelligence (AI) and Financial Digital Twin (FDT) are emerging technologies with significant potential to enhance the effectiveness of credit risk monitoring in modern banking systems. This study aims to analyze research developments related to the application of AI and FDT in credit risk monitoring and to develop a conceptual framework for an AI-based Financial Digital Twin in banking systems. The study employs the Systematic Literature Review (SLR) method based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Research data were obtained from 20 relevant scientific articles addressing AI, machine learning, XAI, digital twins, and banking risk management. The findings indicate that AI has become a key technology in credit risk assessment through the implementation of machine learning, deep learning, and predictive analytics, which improve the accuracy of credit risk prediction. Furthermore, XAI contributes to enhancing the transparency and interpretability of AI models in credit decision-making processes. This study proposes a conceptual framework consisting of a data input layer, AI analytics layer, Financial Digital Twin layer, predictive risk system, early warning system, and decision support system to support more adaptive, transparent, and proactive credit risk monitoring practices.Kata kunci: Artificial Intelligence; Financial Digital Twin; Credit Risk; Banking; Explainable Artificial Intelligence
Digital Transformation for the Future of the Manufacturing Industry in Merauke Regency Caecilia Henny; Okto Irianto; Mensy Otelyo Kastanya; Harmiza Erziena
Journal of International Conference Proceedings Vol 9, No 2 (2026): 2026 Vietnam ICPM Proceeding
Publisher : AIBPM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32535/jicp.v9i3.4771

Abstract

ABSTRACT This study aims to examine the opportunities, challenges, and strategies for implementing digital transformation in Merauke's manufacturing sector. A qualitative descriptive approach is applied, using literature review, policy analysis, and relevant studies on industrial digitalization. The findings indicate that technologies such as Internet of Things (IoT), Artificial Intelligence (AI), cloud computing, big data analytics, and automation significantly improve production efficiency, product quality, and industrial competitiveness while expanding market access through digital platforms and e-commerce. Effective implementation requires strong collaboration among government, industry, educational institutions, and local communities. Keywords: digital transformation, manufacturing industry, Industry 4.0, Merauke, smart manufacturing

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