Indonesia Population Density Map Visualization

Introduction

This document presents a visualization of Indonesia’s population density using provincial population density data and the Indonesia administrative boundary map from GADM.

Load Required Packages

library(sf)
library(dplyr)
library(ggplot2)
library(viridis)

Import Population Density Data

population_data <- read.csv(
  "C:/Users/rayha/Downloads/kepadatan (1).csv",
  stringsAsFactors = FALSE
)

head(population_data)

##                      Region kepadatan
## 1                      ACEH        86
## 2                      BALI       718
## 3 KEPULAUAN BANGKA BELITUNG        84
## 4                    BANTEN      1237
## 5                  BENGKULU        94
## 6                 GORONTALO       101

Prepare Province Names

# Convert province names to uppercase
population_data$Region <- toupper(population_data$Region)

# Remove spaces to match GADM province names
population_data$Region <- gsub(" ", "", population_data$Region)

# Rename several provinces to match GADM naming
population_data$Region <- recode(
  population_data$Region,
  "KEPULAUANBANGKABELITUNG" = "BANGKABELITUNG",
  "DKIJAKARTA" = "JAKARTARAYA",
  "DIYOGYAKARTA" = "YOGYAKARTA"
)

Create Population Density Categories

population_data$DensityGroup <- cut(
  population_data$kepadatan,
  breaks = c(-Inf, 51, 251, 401, Inf),
  labels = c(
    "Low",
    "Moderate",
    "High",
    "Very High"
  )
)

table(population_data$DensityGroup)

## 
##       Low  Moderate      High Very High 
##         8        17         1         7

Import Indonesia Administrative Map

indonesia_map <- st_read(
  "C:/Users/rayha/Downloads/gadm41_IDN_1.json",
  quiet = TRUE
)

Prepare Province Names in the Map

indonesia_map$Region <- toupper(as.character(indonesia_map$NAME_1))

# Remove spaces
indonesia_map$Region <- gsub(" ", "", indonesia_map$Region)

Remove North Kalimantan

# North Kalimantan was established after 2015
indonesia_map <- subset(
  indonesia_map,
  Region != "KALIMANTANUTARA"
)

Merge Spatial and Population Data

merged_map <- left_join(
  indonesia_map,
  population_data,
  by = "Region"
)

Check Missing Provinces

sum(is.na(merged_map$DensityGroup))

## [1] 0

merged_map$Region[
  is.na(merged_map$DensityGroup)
]

## character(0)

Population Density Map (Categorical)

ggplot(merged_map) +
  geom_sf(aes(fill = DensityGroup)) +
  scale_fill_viridis_d(option = "D") +
  labs(
    title = "Indonesia Population Density Map (2015)",
    fill = "Category"
  ) +
  theme_minimal()

Interpretation

The map classifies Indonesian provinces into four population density categories: Low, Moderate, High, and Very High.

Most provinces located in Kalimantan, Maluku, and Papua fall into the Low population density category, indicating relatively small populations compared with their land area.

Several provinces in Sumatra, Sulawesi, and Nusa Tenggara belong to the Moderate category, while the High category is represented by only a few provinces.

The Very High category is concentrated on Java Island, reflecting its role as Indonesia’s primary center for government, economic activity, education, and industry. Consequently, these provinces have much higher population densities than other regions.

Overall, the map shows that population density in Indonesia is unevenly distributed, with the highest concentration occurring on Java Island and lower densities observed across much of eastern Indonesia.