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All Journal Ability : Journal of Education and Social Analysis JagoMIPA: Jurnal Pendidikan Matematika dan IPA COMSERVA: Jurnal Penelitian dan Pengabdian Masyarakat Jurnal Indonesia Sosial Teknologi Jurnal Indonesia Sosial Sains Journal Research of Social Science, Economics, and Management Jurnal Pendidikan Indonesia (Japendi) Equivalent: Jurnal Ilmiah Sosial Teknik Jurnal Teknik Indonesia El-Mal: Jurnal Kajian Ekonomi & Bisnis Islam Insight : International Journal of social research Nursing Arts Hospitality Management and Operations Journal Jurnal Farmasi Sains dan Terapan (Journal of Pharmacy Science and Practice) Journal of Artificial Intelligence Research
Solikhah, Mar’atus
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Business Intelligence Models to Support the Digital Transformation of MSMEs in Indonesia in the Digital Economy Era Solikhah, Mar’atus
Jurnal Indonesia Sosial Teknologi Vol. 6 No. 12 (2025): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v6i12.9177

Abstract

The background of this research is motivated by the increasingly rapid digital transformation in various sectors, including in the MSME industry in Indonesia. Although the MSME sector makes a significant contribution to the economy, many MSME actors have difficulty in implementing digital technology effectively, especially in data-driven decision-making. One of the solutions that can support this digital transformation is Business Intelligence (BI) based on Big Data Analytics, which allows MSMEs to manage big data and increase operational efficiency and competitiveness. The purpose of this research is to develop a Business Intelligence (BI) model that can be adopted by MSMEs in Indonesia to support their digital transformation in the digital economy era. This study uses a quantitative approach with an explanatory research design, as well as Structural Equation Modeling (SEM-PLS) to test the relationship between variables that affect the adoption of BI in the MSME sector. The results of the study show that Business Intelligence based on Big Data Analytics has a significant influence on the digital transformation of MSMEs in Indonesia, especially in improving data-based decision-making and operational efficiency. The proposed BI model is proven to support MSMEs to adapt to market dynamics and increase their competitiveness.
Business Intelligence Models to Support the Digital Transformation of MSMEs in Indonesia in the Digital Economy Era Solikhah, Mar’atus; Maulana, Sandi Agus
Jurnal Indonesia Sosial Teknologi Vol. 7 No. 2 (2026): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v7i2.9178

Abstract

The background of this research is motivated by the increasingly rapid digital transformation in various sectors, including in the MSME industry in Indonesia. Although the MSME sector makes a significant contribution to the economy, many MSME actors have difficulty in implementing digital technology effectively, especially in data-driven decision-making. One of the solutions that can support this digital transformation is Business Intelligence (BI) based on Big Data Analytics, which allows MSMEs to manage big data and increase operational efficiency and competitiveness. The purpose of this research is to develop a Business Intelligence (BI) model that can be adopted by MSMEs in Indonesia to support their digital transformation in the digital economy era. This study uses a quantitative approach with an explanatory research design, as well as Structural Equation Modeling (SEM-PLS) to test the relationship between variables that affect the adoption of BI in the MSME sector. The results of the study show that Business Intelligence based on Big Data Analytics has a significant influence on the digital transformation of MSMEs in Indonesia, especially in improving data-based decision-making and operational efficiency. The proposed BI model is proven to support MSMEs to adapt to market dynamics and increase their competitiveness.
Generative AI Integration in the Startup Ecosystem: A Technopreneurship Strategy to Increase Global Competitiveness Fauziyyah, Ghina; Solikhah, Mar’atus
International Journal of Social Research Vol. 4 No. 1 (2026): Insight : International Journal of Social Research
Publisher : Worldwide Research Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59888/insight.v4i1.96

Abstract

The rapid development of Generative Artificial Intelligence (Generative AI) technology has driven significant transformations in the global startup ecosystem. This technology enables the automation of creative processes, faster data analysis, and more efficient digital product development. In the context of technopreneurship, the integration of generative AI is a strategic factor that can increase startups' innovation capacity while strengthening global competitiveness. However, understanding how the integration of generative AI technology can be optimized in technopreneurship strategies to improve startup competitiveness still requires more in-depth empirical studies. This study aims to analyze the influence of generative AI integration in the startup ecosystem on technopreneurship strategies and its impact on increasing startups' global competitiveness. This study uses a quantitative approach with an explanatory research method. Data were collected through a survey of founders and managers of technology-based startups that utilize digital innovation in their business activities. The sampling technique used purposive sampling with a total of 150 startups as respondents. Data analysis was conducted using the Structural Equation Modeling–Partial Least Squares (SEM-PLS) method to test the relationship between the research variables. The results of the study indicate that the integration of generative AI has a positive and significant impact on technopreneurship strategies and startups' global competitiveness. Furthermore, technopreneurship strategies are proven to act as a mediating factor, strengthening the relationship between the use of generative AI technology and increased startup competitiveness in the global market. These findings suggest that the use of generative AI, supported by innovative technological entrepreneurship strategies, can be a source of competitive advantage for startups in facing the dynamics of the global digital economy.
Co-Authors Ainul Kholipah, Siti Amelia Amelia Apit Afifah, Timbang Asri Arbie Baitul Jannah, Khofifah Indah Dwi Putri Pramesti, Ginna Novarianti Faransisca, Vika Fauziyyah, Ghina Hossain, Md. Jakir Luthfiah Luthfiah Masrid Pikoli Maulana, Sandi Agus Muawanah Muawanah Rehman, Atif Rizqi Alvian Fabanyo Sairmau, Gerson Titus Shofwa Shafrani, Yoiz Sundari Sundari Tamamiyah, Lutfiyatut Teguh Widodo Yusuf, Frita Fauzi