Data Analysis using Business Intelligence and Tableau for Visualizing Indonesia's Poverty Line

Fabianus Kevin Senduk, Retno Waluyo, Khairunnisak Nur Isnaini

Abstract


Poverty is the condition of being unable to meet an adequate standard of living. The poverty line serves as a key indicator for measuring poverty, particularly in developing countries. In Indonesia, poverty line data provided by the Central Statistics Agency (Badan Pusat Statistik – BPS) is typically presented in static tables, lacking in-depth analysis or annual trend insights needed to understand poverty dynamics across 578 regions. This study aims to analyze poverty line data in Indonesia using a Business Intelligence (BI) approach and visualize it through Tableau Public. BI was chosen for its capability to process complex data into more accessible and actionable information for decision-making. The output of this study is an interactive visualization dashboard that illustrates the distribution patterns and trends of the poverty line in Indonesia over the period 2022–2024. The dashboard offers in-depth insights into regional poverty shifts, including the identification of high-poverty areas and analysis of poverty line growth rates. It also serves as a strategic data-driven decision support tool. This research can be further developed by exploring the underlying factors driving poverty line fluctuations, applying the method to other dimensions such as income inequality, and leveraging alternative data visualization tools for a more comprehensive analysis.

Keywords


Business Intelligence; Visualisasi Data; Analisis Data; Tableau

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DOI: https://doi.org/10.32520/stmsi.v14i3.4993

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