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The Effect of Security Levels, Resource Requirements, and Scalability on User Acceptance of Cloud Computing Systems in Technology Companies in Indonesia Muhamad Bakhar; Muchamad Sobri Sungkar
West Science Interdisciplinary Studies Vol. 1 No. 12 (2023): West Science Interdisciplinary Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsis.v1i12.509

Abstract

This research investigates the impact of security levels, resource requirements, and scalability on user acceptance of cloud computing systems in technology companies in Indonesia. Employing a quantitative approach, the study involves a sample of 250 respondents from diverse companies. The research employs Structural Equation Modeling with Partial Least Squares (SEM-PLS) for data analysis. Descriptive statistics, measurement model assessment, discriminant validity analysis, and structural model assessment are conducted to explore relationships between variables. Results reveal significant positive relationships between security levels, resource requirements, scalability, and user acceptance. The study provides insights into the critical factors influencing cloud computing adoption in Indonesia's dynamic technological landscape.
Analysis of the Influence of Artificial Intelligence (AI), Machine Learning, and Data Analytics on Marketing Performance at Technology Start-Ups in Jakarta Muchamad Sobri Sungkar; Mukrodin Mukrodin; Muhamad Bakhar
West Science Information System and Technology Vol. 2 No. 03 (2024): West Science Information System and Technology
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsist.v2i03.1479

Abstract

The integration of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Data Analytics has transformed marketing practices, especially in technology-driven sectors like start-ups. This study examines the influence of these technologies on marketing performance in technology start-ups in Jakarta using quantitative analysis. Data were collected from 150 respondents through a structured questionnaire and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS 3). The findings reveal that AI, ML, and Data Analytics each have significant positive impacts on marketing performance, with Data Analytics emerging as the strongest individual predictor. Moreover, the combined use of these technologies demonstrates a synergistic effect, amplifying their overall influence. These results highlight the critical role of technology integration in enhancing marketing efficiency, customer engagement, and return on investment. The study contributes to the theoretical understanding of technology adoption in marketing and provides actionable insights for start-ups aiming to leverage these tools for competitive advantage.