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p-Index From 2021 - 2026
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All Journal Journal of Indonesian Applied Economics JAT (Journal of Accounting and Tax)
Alissa Qodrunnada
Universitas Airlangga
Economics, Econometrics & Finance

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Impact of Decrease in Cultural Tourism Visits on Gross Regional Domestic Product of Blitar Regency During The Covid-19 Pandemic Siti Arifah; Ilmiawan Auwalin; Alissa Qodrunnada; Rezhi Vauzi
Journal of Indonesian Applied Economics Vol. 10 No. 1 (2022)
Publisher : Department of Economics, Faculty of Economics and Business, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jiae.2022.010.01.1

Abstract

The COVID-19 virus has become a global pandemic and has spread to various countries, including Indonesia. The pandemic causes turmoil in the health sector and the economy. The impacts of the pandemic are not only at the national level but also the provincial and district level. The district of Blitar is no exception. Blitar is a district in East Java Province with a diverse cultural heritage. Cultural tourism directly contributes to the regional revenue, which can help the recovery of the local economy. This study examines the impact of the COVID-19 pandemic on the number of cultural tourism visits and its implications on the Gross Regional Domestic Product (GRDP) of Blitar. The results show that while the tourist visits contribute to the GRDP of Blitar, the contribution has been negatively impacted by the pandemic.
ARTIFICIAL INTELLIGENCE AND PUBLIC SECTOR ORGANIZATIONAL PERFORMANCE: A SYSTEMATIC LITERATURE REVIEW Alissa Qodrunnada; Isnalita
JAT : Journal Of Accounting and Tax Vol. 5 No. 2 (2026): Special Issue
Publisher : Universitas Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36563/aja8rz76

Abstract

This study aims to systematically map the Scopus-indexed literature on artificial intelligence and organizational performance in the public sector and to identify the mechanisms that explain the relationship between AI and organizational performance. A systematic literature review approach based on the PRISMA guidelines was used to identify, select, and synthesize relevant articles. The thematic synthesis indicates that the relationship between AI and organizational performance can be understood through several interrelated themes, including AI-based organizational capabilities, good governance, public values and the governance of automated systems, human resources and leadership, as well as innovation and knowledge management. The results of the synthesis indicate that the benefits of AI on performance are not universal but depend on organizational capabilities, the quality of governance, and the readiness of data and systems. Empirical evidence also remains concentrated in specific national contexts, while evidence regarding the context of local government in Indonesia remains limited. Based on these findings, this study formulates theoretical propositions grounded in Dynamic Capability Theory, which positions organizational capabilities as a key mechanism and governance and institutional context as conditions that can influence the relationship between AI and performance. These findings provide direction for the development of empirical models of AI and organizational performance in the public sector, particularly in Indonesian local governments.
Co-Authors Ilmiawan Auwalin Isnalita Rezhi Vauzi Siti Arifah