Data = read.table(file.choose(), header = TRUE, sep = ",")
Data
## Provinsi Perkotaan Perdesaan Jumlah
## 1 ACEH 8.27 14.66 12.34
## 2 SUMATERA UTARA 7.05 7.17 7.10
## 3 SUMATERA BARAT 3.82 6.88 5.27
## 4 RIAU 5.26 6.83 6.19
## 5 JAMBI 9.07 5.45 6.67
## 6 SUMATERA SELATAN 8.48 10.13 9.50
## 7 BENGKULU 12.73 11.37 11.83
## 8 LAMPUNG 7.28 10.41 9.31
## 9 KEP. BANGKA BELITUNG 3.53 6.54 4.75
## 10 KEP. RIAU 3.68 8.65 4.09
## 11 DKI JAKARTA 3.96 NA 3.96
## 12 JAWA BARAT 6.32 7.48 6.54
## 13 JAWA TENGAH 8.59 9.96 9.21
## 14 DI YOGYAKARTA 9.55 10.18 9.70
## 15 JAWA TIMUR 6.66 12.38 9.06
## 16 BANTEN 5.21 6.23 5.38
## 17 BALI 3.06 4.54 3.44
## 18 NUSA TENGGARA BARAT 11.25 11.08 11.17
## 19 NUSA TENGGARA TIMUR 6.71 21.64 17.52
## 20 KALIMANTAN BARAT 4.32 6.72 5.78
## 21 KALIMANTAN TENGAH 4.86 5.27 5.09
## 22 KALIMANTAN SELATAN 2.81 4.50 3.63
## 23 KALIMANTAN TIMUR 4.15 7.42 5.14
## 24 KALIMANTAN UTARA 5.42 4.73 5.18
## 25 SULAWESI UTARA 3.85 9.59 6.32
## 26 SULAWESI TENGAH 6.62 12.48 10.46
## 27 SULAWESI SELATAN 4.65 9.72 7.24
## 28 SULAWESI TENGGARA 6.17 12.83 10.02
## 29 GORONTALO 4.30 19.24 12.16
## 30 SULAWESI BARAT 7.90 10.57 10.00
## 31 MALUKU 3.99 24.10 14.91
## 32 MALUKU UTARA 6.00 5.69 5.79
## 33 PAPUA BARAT 8.14 23.71 18.68
## 34 PAPUA BARAT DAYA 7.48 30.18 16.49
## 35 PAPUA 6.09 38.19 18.39
## 36 PAPUA SELATAN 4.00 25.77 18.54
## 37 PAPUA TENGAH 4.18 39.37 30.41
## 38 PAPUA PEGUNUNGAN 16.72 27.95 26.34
library(ggplot2)
ggplot(Data, aes(x = Jumlah)) +
geom_histogram(
binwidth = 5,
boundary = 0,
fill = "pink",
color = "black"
) +
scale_x_continuous(
breaks = seq(0, 35, by = 5),
limits = c(0, 35)
) +
labs(
title = "Persentase Penduduk Miskin di Indonesia",
x = "Persentase Penduduk Miskin (%)",
y = "Freq"
) +
theme_classic() +
theme(
axis.text.x = element_text(angle = 0, hjust = 0.5),
plot.title = element_text(hjust = 0.5, face = "bold")
)
ggplot(Data, aes(x = "", y = Jumlah)) +
geom_boxplot(fill = "pink") +
labs(title = "Box Plot Persentase Penduduk Miskin Indonesia 2026", x = "", y = "Persentase (%)") +
theme_minimal() +
theme(plot.title = element_text(hjust = 0.5, face = "bold"))
library(dplyr)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats 1.0.1 ✔ stringr 1.5.2
## ✔ lubridate 1.9.4 ✔ tibble 3.3.0
## ✔ purrr 1.1.0 ✔ tidyr 1.3.1
## ✔ readr 2.1.5
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(ggplot2)
Data_Kalimantan <- Data %>%
filter(str_starts(Provinsi, "KALIMANTAN"))
Data_Kalimantan
## Provinsi Perkotaan Perdesaan Jumlah
## 1 KALIMANTAN BARAT 4.32 6.72 5.78
## 2 KALIMANTAN TENGAH 4.86 5.27 5.09
## 3 KALIMANTAN SELATAN 2.81 4.50 3.63
## 4 KALIMANTAN TIMUR 4.15 7.42 5.14
## 5 KALIMANTAN UTARA 5.42 4.73 5.18
ggplot(Data_Kalimantan, aes(x = Provinsi, y = Jumlah, fill = Provinsi)) +
geom_col() +
labs(
title = "Persentase Penduduk Miskin Pulau Kalimantan Tahun 2026",
x = "Provinsi",
y = "Persentase (%)"
) +
theme_minimal() +
theme(
axis.text.x = element_text(angle = 45, hjust = 1),
plot.title = element_text(hjust = 0.5, face = "bold"),
legend.position = "none"
)
