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Data Viz and Storytelling

Part 2 — An Overview of Indonesia’s Natural Disasters Trends and Insights Over the Last 21 Years

Explore the big pictures of disasters in Indonesia through data visualization with Plotly

Audhi Aprilliant
7 min readAug 1, 2022

In Part 1, we have already discussed the general overview of Indonesia’s natural disaster trends from 2000 to 2021, including some tragic and unforgettable incidents. In this part, we will delve into more granular data and aim to understand the characteristics of disasters, provinces, and districts in Indonesia in terms of victims and property losses. In most cases, the insights gained from visualizations are connected to the previous findings, as they provide a holistic understanding of the phenomenon, reinforcing each other and capturing the big picture.

Statistically, the disasters that have occurred over the last 21 years in Indonesia resulted in a total of 2,051 victims and 3,916 property losses, with floods, landslides, and tornadoes being the major contributors

In the figure below, we have created four quadrants that describe the characteristics of disasters based on their property losses and number of victims. These quadrants are defined by two vertical lines, where the former indicates the average number of victims of disasters over the last 21 years (2,051 victims) and the latter represents the average amount of property losses from disasters over the same period (3,916 properties). This arrangement results in four specific areas above or below these lines, forming the quadrants.

Among the 12 disasters studied, three of them fall into the first quadrant, which represents an area with a high number of victims and significant property losses. These three disasters are floods, tornadoes, and landslides. Landslide disasters, in particular, have the highest amount of property losses, with 12,961 properties damaged over the last 21 years, averaging to 618 properties damaged every year. These landslides occur in both lightly and heavily damaged areas, often located on mountain slopes with unstable ground, caused by factors such as…



Audhi Aprilliant

Data Scientist. Tech Writer. Statistics, Data Analytics, and Computer Science Enthusiast. Portfolio & social media links at