Application of Statistical Analysis in Information Systems to Support Data-Driven Decision Making: A Literature Study - Ade Putra Syawaludin; Arif Setiabudi; Purwadi Purwadi (Lembaga Yasin AlSys, 2026)
Although information systems are increasingly used to support organizational decision processes, understanding of how statistical analysis is applied within these systems and how it contributes to decision quality remains limited. This study aims to examine the application of statistical analysis in information systems to support data-driven decision making. Using a literature review approach, this study analyzes relevant scientific articles on statistical analysis, information systems, business intelligence, decision support systems, and data-driven decision making. The findings indicate that statistical analysis plays a central role in transforming data into meaningful information through descriptive analysis, correlation, regression, prediction, classification, and data visualization. Its integration into information systems enables organizations to understand actual conditions, identify patterns, estimate trends, and formulate more objective decision recommendations. This study concludes that the integration of statistical analysis in information systems can improve evidence-based, measurable, and organizationally relevant decision making. The study contributes to the literature by clarifying the analytical role of statistical methods in information systems and provides practical implications for organizations seeking to strengthen decision quality through data-driven approaches.