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Evolution of the Use of Artificial Intelligence in Mobile Applications to Improve the Efficiency of Public Service Loso Judijanto; Arief Yanto Rukmana; Aldi Bastiatul Fawait; Sitti Rahmah; Sugiarto Sugiarto
West Science Social and Humanities Studies Vol. 2 No. 11 (2024): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v2i11.1457

Abstract

The integration of artificial intelligence (AI) into mobile applications has transformed public service delivery by enhancing efficiency, accessibility, and responsiveness. This study employs a bibliometric approach to analyze the evolution of AI applications in public service, focusing on research trends, key contributors, and thematic developments from 2000 to 2024. The findings reveal a rapid increase in research output since 2018, driven by advancements in enabling technologies such as IoT, 5G, and machine learning, as well as global challenges like the COVID-19 pandemic. Key application areas identified include healthcare, smart cities, and governance, with AI-powered mobile apps demonstrating significant potential in addressing societal needs. However, challenges related to data privacy, algorithmic bias, and technical infrastructure persist. This study underscores the importance of ethical frameworks, interdisciplinary collaboration, and localized solutions to maximize the impact of AI in public service delivery. The findings offer valuable insights for researchers, practitioners, and policymakers seeking to leverage AI for smarter and more equitable public services.
PENILAIAN KESEHATAN KEUANGAN PADA PERUSAHAAN ASURANSI UMUM Agus Riyanto; Siti Rohmah; Sri Wahyuti; Sugiarto Sugiarto
Jurnal Ekonomika: Manajemen, Akuntansi, dan Perbankan Syari'ah Vol. 14 No. 2 (2025): September
Publisher : Economic Faculty, University of Widya Gama Mahakam Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24903/je.v14i2.3620

Abstract

The purpose of this study is to see the health of general insurance companies by calculating Risk Based Capital, where Risk Based Capital is a measurement of the health of the insurance company's finances by calculating the amount of permitted assets minus permitted liabilities and dividing it by the Minimum Risk Based Capital (MMBR). Minimum Risk Based Capital is the total funds needed to maintain losses that will occur due to deviations or violations when assets and liabilities are managed. From a population of 18 insurance companies, 13 general insurance companies were selected. From the results of the analysis, it is known that general insurance companies listed on the Indonesia Stock Exchange are in very healthy, healthy, and fairly healthy conditions, as evidenced by the solvency ratio or health level of each general insurance company being above 120%, which means that the company's obligations are well met.