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All Journal Journal of Tabulation Economic Data Digital Business and Innovation Journal
Abdul Salam
Institut Agama Islam Negeri Kendari

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Analisis Kualitatif Kesenjangan Pemahaman antara Indikator Ekonomi Makro Nasional dan Realitas Ekonomi Lokal: Studi Kasus Pantai Nambo Kota Kendari Irwan W; Abdul Salam; Alfin Siolimbona
Journal of Tabulation Economic Data Vol. 2 No. 1 (2026)
Publisher : Akademi Bisnis Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67462/1jqvm451

Abstract

Indikator ekonomi makro nasional, seperti pertumbuhan ekonomi, inflasi, dan tingkat pengangguran, sering digunakan untuk mengukur kinerja perekonomian. Namun, indikator tersebut belum sepenuhnya mencerminkan kondisi ekonomi masyarakat di tingkat lokal. Penelitian ini bertujuan menganalisis kesenjangan antara indikator ekonomi makro nasional dan realitas ekonomi lokal serta mengidentifikasi faktor-faktor yang memengaruhinya. Penelitian menggunakan pendekatan kualitatif dengan desain studi kasus. Data diperoleh melalui wawancara mendalam, observasi, dan studi dokumentasi, kemudian dianalisis menggunakan model interaktif Miles, Huberman, dan Saldaña. Hasil penelitian menunjukkan bahwa pertumbuhan ekonomi nasional yang positif belum diikuti oleh peningkatan kesejahteraan masyarakat di daerah. Kesenjangan tersebut ditandai oleh terbatasnya kesempatan kerja, rendahnya daya beli, ketidakstabilan pendapatan, dan tingginya biaya hidup. Kondisi ini dipengaruhi oleh struktur ekonomi lokal, ketimpangan akses terhadap infrastruktur dan pasar, serta distribusi manfaat pembangunan yang belum merata. Penelitian ini menyimpulkan bahwa evaluasi pembangunan perlu mengintegrasikan indikator ekonomi makro dengan indikator kesejahteraan lokal agar kebijakan ekonomi lebih inklusif, tepat sasaran, dan sesuai dengan kebutuhan masyarakat daerah.
Generative Artificial Intelligence for Digital Business Innovation: A Systematic Literature Review Bayu Erwinadi; Alfin Siolombona; Abdul Salam
Jurnal Sistem dan Inovasi Digital Vol 1 No 1 (2026): Digital Business and Innovation Journal (DIBI)
Publisher : Lembaga Penelitian dan Pendidikan (LPP) Mandala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58258/dibi.s8pbr504

Abstract

Generative Artificial Intelligence (Generative AI) has emerged as a transformative technology that is reshaping digital business innovation by enabling organizations to enhance creativity, optimize decision-making, redesign business models, and improve operational efficiency. Despite the rapid growth of research in this area, existing studies remain fragmented across different business contexts and disciplines, limiting a comprehensive understanding of its strategic role. This study aims to synthesize the current body of knowledge on Generative AI for digital business innovation through a Systematic Literature Review (SLR). Following the PRISMA 2020 guidelines, peer-reviewed journal articles indexed in Scopus and published between 2024 and 2026 were systematically identified, screened, and analyzed using thematic content analysis. A total of 50 articles met the inclusion criteria and were included in the qualitative synthesis. The analysis identified six interconnected themes: Business Innovation, Organizational Capability, Organizational Intelligence, Human–AI Collaboration, Responsible AI Governance, and Business Performance. The findings indicate that Generative AI functions not merely as an automation technology but as a strategic organizational capability that supports sustainable digital transformation and competitive advantage. This review contributes by proposing an integrated conceptual framework that explains how Generative AI creates organizational value through the interaction of technological capability, organizational readiness, knowledge management, innovation capability, governance, and human collaboration, while also identifying key research gaps and directions for future studies.
Co-Authors Alfin Siolimbona Alfin Siolombona Bayu Erwinadi Irwan W