Aklani , Syaeful Anas
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Analysis of Tableau Dashboard Visualization for Efficiency and Accuracy in Industrial Decision Making Susanto, Dedy; Aklani , Syaeful Anas; Siahaan, Mangapul
Jurnal Teknologi Informatika dan Komputer Vol. 12 No. 1 (2026): Jurnal Teknologi Informatika dan Komputer
Publisher : Universitas Mohammad Husni Thamrin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37012/jtik.v12i1.3223

Abstract

As data complexity increases, Tableau-based data visualization dashboards play an important role in simplifying information and improving understanding for decision makers. This study uses a mixed methods approach by combining quantitative data from 154 questionnaire respondents and qualitative data through in-depth interviews with five informants from various industrial sectors. Statistical analysis using SmartPLS shows that ease of data comprehension has a significant effect on efficiency (coefficient = 0.703) and decision-making accuracy (coefficient = 0.566), while Tableau dashboard visualization has a positive but more moderate effect (coefficient = 0.207). Qualitative results reinforce these findings, where the application of interactive dashboards has been proven to accelerate the analysis process, reduce interpretation errors, and improve communication between departments within the organization. In addition, real-time data access helps decision makers obtain information more quickly and reliably. However, there are still challenges in implementing data visualization, particularly limitations in digital literacy and technological infrastructure. Therefore, effective data visualization integration needs to be accompanied by technical training and user competency improvement in order to optimize its benefits in the modern industrial era. The results of this study provide practical implications for industry in improving operational performance and the quality of data-based decision making.