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The Role of Business Incubators in Developing Local Digital Startups in Indonesia Anwar, Muhammad Rehan; Yusup, Muhamad; Millah, Shofiyul; Purnama, Suryari
Startupreneur Business Digital (SABDA Journal) Vol. 1 No. 1 (2022): Startupreneur Business Digital (SABDA)
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1278.017 KB) | DOI: 10.33050/sabda.v1i1.69

Abstract

The development of the internet causes the flow of information to move quickly without knowing geographical boundaries. Likewise with the development of the digital industry, although the condition of the digital industry in Indonesia is still in its early phase, where infrastructure and ecosystem support is still very minimal, the optimism from digital industry players in Indonesia is very strong, both from the startup side and from investors. Problems arise when investors, both local and foreign, wish to invest in local digital startups in Indonesia, namely the unpreparedness of local startups to receive relatively large amounts of funding for business development. This raises doubts for investors whether startups can manage the funds raised and generate future profits for investors. Therefore, an initiative was born from investors and stakeholders in the digital technology industry to activate business incubators, with the aim of being able to prepare local startups to be able to develop more optimally. The results of this study reveal various tangible benefits received by local startups to increase their capacity.
Integrating Artificial Intelligence and Environmental Science for Sustainable Urban Planning Anwar, Muhammad Rehan; Sakti, Lintang Dwi
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 5 No 2 (2024): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v5i2.666

Abstract

The rapid urbanization of modern cities presents significant challenges in sustainable development. To address these challenges, there is a growing integration of Artificial Intelligence (AI) and Environmental Science to enhance urban planning processes. This research aims to assess the impact and utility of AI techniques within the framework of Geographic Information Systems (GIS) for sustainable urban planning. Specifically, it investigates how AI-enhanced GIS tools can be employed to improve urban development strategies and enhance sustainability assessments. Employing Spatial Analysis with GIS, this study analyzes data on land use, population density, and environmental indicators across several metropolitan areas. The methodology incorporates machine learning algorithms to predict and simulate urban growth patterns, enabling the assessment of various urban planning scenarios. The findings reveal that AI-enhanced GIS tools significantly improve the precision of development forecasts and sustainability assessments. These tools facilitate more informed decision-making in urban planning by enabling precise predictions about urban expansion and its environmental impacts. The integration of AI with environmental science not only enhances the efficiency of urban planning processes but also contributes to the resilience and sustainability of urban environments. The study provides urban planners and policymakers with advanced tools to forecast and mitigate the environmental impacts of urbanization, thereby setting a benchmark for future studies in the realm of sustainable urban planning. This research demonstrates the practical application of AI in enhancing the capabilities of GIS for complex spatial analyses, contributing significantly to the field of urban planning.