<![CDATA[In today's digital era, statistical literacy has become a crucial competence for individuals to understand and interpret data-based information presented in tables, graphs, and diagrams. Although data representation is a fundamental part of the Junior High School (SMP) mathematics curriculum, reality in the field indicates that many students still face obstacles in critically interpreting data. Student understanding is often limited to reading data explicitly, lacking the ability to perform deeper evaluation or analysis. This study aims to analyze the level of Junior High School students' understanding of statistical data representation, identify the types of difficulties students face in interpreting data visualizations, and explore the various factors influencing their level of comprehension. In order to give a comprehensive summary of the respondents' situations, this study utilized a descriptive methodology with a qualitative approach. During the 2025–2026 school year, researchers at SMP Fitra Abdi Palembang collected data. Students in the high, medium, and low understanding groups were included in the subject selection process through the use of a purposive sampling technique. To begin, we used a questionnaire to collect basic information on students' perspectives; to round up our data, we used semi-structured interviews to confirm students' reasoning behind their responses. Indicators of mathematical competence, such as the capacity to categorize objects, choose operational processes, and apply algorithms for solving problems, were considered in the data analysis procedures that comprised data reduction, data presentation, and drawing conclusions. This study aims to assess students' statistical literacy in a comprehensive way. By doing so, we can help junior high school teachers enhance their data analysis skills through the development of more contextual and effective learning methodologies.]]>
