Data yang digunakan merupakan angka random dari R Studio
# Load necessary libraries
library(ggplot2)
# Create sample data
set.seed(123)
data <- data.frame(
x = rnorm(100, mean = 50, sd = 10),
y = rnorm(100, mean = 30, sd = 5)
)
# Scatter plot
ggplot(data, aes(x = x, y = y)) +
geom_point(color = "blue") +
labs(title = "Scatter Plot of x vs y", x = "x", y = "y") +
theme_minimal()
# Load necessary libraries
library(ggplot2)
library(reshape2)
# Create sample data
data_pengeluaran <- data.frame(
Pengeluaran_Pedesaan = c(500, 550, 600, 620, 680, 700, 750, 800, 850, 900),
Pengeluaran_Perkotaan = c(650, 700, 750, 800, 850, 900, 950, 1000, 1050, 1100)
)
# Scatter plot
scatter_plot <- ggplot(data_pengeluaran, aes(x = Pengeluaran_Pedesaan, y = Pengeluaran_Perkotaan)) +
geom_point(color = "blue") +
labs(title = "Scatter Plot Pengeluaran Pedesaan vs Perkotaan",
x = "Pengeluaran Pedesaan (ribu IDR)",
y = "Pengeluaran Perkotaan (ribu IDR)") +
theme_minimal()
# Melt the data for easier plotting
data_pengeluaran_melt <- melt(data_pengeluaran)
## No id variables; using all as measure variables
# Histogram
histogram_plot <- ggplot(data_pengeluaran_melt, aes(x = value, fill = variable)) +
geom_histogram(position = "identity", alpha = 0.5, bins = 10) +
labs(title = "Histogram Pengeluaran Pedesaan dan Perkotaan",
x = "Pengeluaran (ribu IDR)",
y = "Frekuensi",
fill = "Kategori") +
theme_minimal()
# Print plots
print(scatter_plot)
print(histogram_plot)