TMKomstat_2

Data <- read.table(file.choose(), header = TRUE, sep = "\t")
Data

##                Provinsi Sanitasi_layak
## 1                  Aceh          82.21
## 2        Sumatera Utara          87.47
## 3        Sumatera Barat          74.59
## 4                  Riau          91.21
## 5                 Jambi          85.88
## 6      Sumatera Selatan          85.50
## 7              Bengkulu          85.75
## 8               Lampung          87.29
## 9  Kep. Bangka Belitung          96.45
## 10            Kep. Riau          90.96
## 11          DKI Jakarta          93.98
## 12           Jawa Barat          76.20
## 13          Jawa Tengah          87.51
## 14       DI Yogayakarta          96.94
## 15           Jawa Timur          88.26
## 16               Banten          90.71
## 17                 Bali          98.20
## 18                  NTB          88.29
## 19                  NTT          80.80
## 20     Kalimantan Barat          88.37
## 21    Kalimantan Tengah          83.14
## 22   Kalimantan Selatan          86.80
## 23     Kalimantan Timur          92.57
## 24     Kalimantan Utara          86.00
## 25       Sulawesi Utara          87.72
## 26      Sulawesi Tengah          79.62
## 27     Sulawesi Selatan          94.19
## 28    Sulawesi Tenggara          91.96
## 29            Gorontalo          84.70
## 30       Sulawesi Barat          85.98
## 31         Maluku Utara          83.09
## 32         Maluku Utara          84.12
## 33          Papua Barat          78.55
## 34     Papua Barat Daya          79.56
## 35                Papua          76.71
## 36        Papua Selatan          65.06
## 37         Papua Tengah          39.73
## 38    Papua Pengunungan          16.34

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.5.3

ggplot(Data, aes(x = Sanitasi_layak)) +
  geom_histogram(
    binwidth = 5,
    boundary = 60,
    fill = "navyblue",
    color = "white"
  ) +
  scale_x_continuous(
    breaks = seq(60, 85, by = 5),
    limits = c(60, 85)
  ) +
  labs(
    title = "Akses Sanitasi Layak",
    x = "Sanitasi Layak",
    y = "Freq"
  ) +
  theme_classic() +
  theme(
    axis.text.x = element_text(angle = 0, hjust = 0.5),
    plot.title = element_text(
      hjust = 0.5,
      face = "bold"
    )
  )

## Warning: Removed 25 rows containing non-finite outside the scale range
## (`stat_bin()`).

ggplot(Data, aes(x = "", y = Sanitasi_layak)) +
  geom_boxplot(fill = "pink") +
  labs(
    title = "Box plot akses sanitasi layak 2025",
    x = "",
    y = "Akses Sanitasi Layak"
  ) +
  theme_minimal() +
  theme(plot.title = element_text(hjust = 0.5, face = "bold"))

library(dplyr)

## Warning: package 'dplyr' was built under R version 4.5.3

## 
## 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)

## Warning: package 'tidyverse' was built under R version 4.5.3

## Warning: package 'tibble' was built under R version 4.5.3

## Warning: package 'tidyr' was built under R version 4.5.3

## Warning: package 'readr' was built under R version 4.5.3

## Warning: package 'purrr' was built under R version 4.5.3

## Warning: package 'stringr' was built under R version 4.5.3

## Warning: package 'forcats' was built under R version 4.5.3

## Warning: package 'lubridate' was built under R version 4.5.3

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ lubridate 1.9.5     ✔ tibble    3.3.1
## ✔ purrr     1.2.2     ✔ tidyr     1.3.2
## ✔ readr     2.2.0

## ── 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 Sanitasi_layak
## 1   Kalimantan Barat          88.37
## 2  Kalimantan Tengah          83.14
## 3 Kalimantan Selatan          86.80
## 4   Kalimantan Timur          92.57
## 5   Kalimantan Utara          86.00

ggplot(Data_Kalimantan, aes(x = Provinsi, y = Sanitasi_layak, fill=Provinsi)) +
  geom_col() +
  labs(
    title = "Akses Sanitasi Layak Pulau Kalimantan Tahun 2024",
    x = "Provinsi",
    y = "Akses Sanitasi Layak"
  ) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    plot.title = element_text(hjust = 0.5, face = "bold"),
    legend.position = "none"
  )