Visualisasi Geospasial

Sebaran Kepemilikan Mobil di Indonesia pada tahun 2022

# Memuat paket
library(readxl)
library(sf)

## Linking to GEOS 3.11.2, GDAL 3.8.2, PROJ 9.3.1; sf_use_s2() is TRUE

library(ggplot2)
library(rnaturalearth)
library(rnaturalearthdata)

## 
## Attaching package: 'rnaturalearthdata'

## The following object is masked from 'package:rnaturalearth':
## 
##     countries110

# Path ke file Excel Anda
file_path <- "D:/beatrics/jumlah-mobil-di-indonesia-berdasarkan-provinsi-2022.xlsx"

# Membaca data dari file Excel
data <- read_excel(file_path, sheet = 1)

# Menampilkan data awal
head(data)

## # A tibble: 6 × 3
##     No. Provinsi         `Jumlah Mobil`
##   <dbl> <chr>            <chr>         
## 1     1 Jawa Barat       3.814.187     
## 2     2 DKI Jakarta      3.766.059     
## 3     3 Jawa Timur       2.034.087     
## 4     4 Jawa Tengah      1.456.793     
## 5     5 Sumatra Utara    730.953       
## 6     6 Sulawesi Selatan 564.060

# Membaca data dari Excel
data <- read_excel("D:/beatrics/jumlah-mobil-di-indonesia-berdasarkan-provinsi-2022.xlsx")

# Memuat data spasial Indonesia
indo <- ne_states(country = "Indonesia", returnclass = "sf")

# Menggabungkan data mobil dengan data spasial
merged_data <- merge(indo, data, by.x = "name", by.y = "Provinsi", all.x = TRUE)

library(RColorBrewer)

ggplot() +
  geom_sf(data = merged_data, aes(fill = factor(`Jumlah Mobil`))) +
  scale_fill_brewer(palette = "Set1") +
  labs(title = "Jumlah Mobil di Indonesia Berdasarkan Provinsi (2022)",
       fill = "Jumlah Mobil")

## Warning in RColorBrewer::brewer.pal(n, pal): n too large, allowed maximum for palette Set1 is 9
## Returning the palette you asked for with that many colors

ggsave("visualisasi_spasial.png")

## Saving 7 x 5 in image

## Warning in RColorBrewer::brewer.pal(n, pal): n too large, allowed maximum for palette Set1 is 9
## Returning the palette you asked for with that many colors