sis 24(2):

Research Article

Integration of Artificial Intelligence and Macro-Economic Analysis: A Novel Approach with Distributed Information Systems

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  • @ARTICLE{10.4108/eetsis.4452,
        author={Ana Shohibul Manshur Al Ahmad and Loso Judijanto and Dedie Tooy and Purnama Putra and Muhammad Hermansyah and Maria Kumalasanti and Alamsyah Agit},
        title={Integration of Artificial Intelligence and Macro-Economic Analysis: A Novel Approach with Distributed Information Systems},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={11},
        number={2},
        publisher={EAI},
        journal_a={SIS},
        year={2023},
        month={11},
        keywords={Integration, Artificial Intelligence, Macro-Economic, Novel Approach, Distributed Information Systems},
        doi={10.4108/eetsis.4452}
    }
    
  • Ana Shohibul Manshur Al Ahmad
    Loso Judijanto
    Dedie Tooy
    Purnama Putra
    Muhammad Hermansyah
    Maria Kumalasanti
    Alamsyah Agit
    Year: 2023
    Integration of Artificial Intelligence and Macro-Economic Analysis: A Novel Approach with Distributed Information Systems
    SIS
    EAI
    DOI: 10.4108/eetsis.4452
Ana Shohibul Manshur Al Ahmad1,*, Loso Judijanto2, Dedie Tooy3, Purnama Putra4, Muhammad Hermansyah5, Maria Kumalasanti6, Alamsyah Agit7
  • 1: Sebelas Maret University
  • 2: IPOSS Jakarta, Indonesia
  • 3: Sam Ratulangi University
  • 4: Universitas Islam 45 Bekasi
  • 5: Universitas Yudharta Pasuruan
  • 6: Sekolah Tinggi Ilmu Ekonomi SBI Yogyakarta
  • 7: Institut Agama Islam DDI Sidenreng Rappang, Indonesia
*Contact email: shohibulana@gmail.com

Abstract

INTRODUCTION: This study introduces a groundbreaking approach that integrates Artificial Intelligence (AI) with macro-economic analysis to address a critical gap in existing economic forecasting methodologies. By leveraging diverse economic data sources, the study aims to transcend traditional analytical boundaries and provide a more comprehensive understanding of macroeconomic trends. OBJECTIVE: The primary objective is to pioneer a scalable framework for economic data analysis by combining AI with macroeconomic analysis. The study aims to utilize advanced machine learning algorithms to analyze and synthesize macroeconomic indicators, offering enhanced accuracy and predictive power. A key focus is on dynamically incorporating real-time data to adapt to evolving economic landscapes. METHODS: The research employs advanced machine learning algorithms to analyze and synthesize macroeconomic indicators. The integration of AI allows for a more nuanced understanding of complex economic dynamics. The methodology uniquely adapts to real-time data, providing a scalable framework for economic data analysis. RESULTS: The findings demonstrate the model's efficacy in predicting economic trends, surpassing conventional models in both precision and reliability. The study showcases the potential of AI-driven economic analysis to offer insights into economic dynamics with unprecedented accuracy. CONCLUSION: This study significantly contributes to the fields of AI and economics by proposing a transformative approach to macroeconomic analysis. The integration of technology and economics sets a new precedent, paving the way for future innovations in economic forecasting. The research also explores the implications of AI-driven economic analysis for policy-making, emphasizing its potential to inform more effective economic strategies.