Aplikasi Visualisasi Data Berbasis Web dengan Deteksi Otomatis Tipe Data untuk Mendukung Analisis Informasi

Abstract

The rapid growth of data-driven decision making requires systems capable of managing and presenting data in
an effective, flexible, and user-friendly manner. However, variations in dataset characteristics, such as numerical
and categorical data, often pose challenges in selecting appropriate visualization techniques. Therefore, this study
designs and develops a web-based data visualization application equipped with an automatic data type detection
mechanism. The system is able to identify data types automatically and determine suitable visualization forms,
including bar charts, line charts, pie charts, histograms, radar charts, and polar area charts. The developed
application allows users to import datasets, monitor data quality, and perform interactive visual analysis. The
implementation results indicate that the system can present various types of datasets in a structured manner and
assist users in understanding data patterns, trends, and characteristics more quickly and intuitively. Thus, this
application supports visual analytics processes and enhances the effectiveness of information analysis.