TM 2 KOMSTAT

Data=read.table(file.choose(), header = T)
Data

##               PROVINSI  HUNI
## 1                 ACEH 71.15
## 2       SUMATERA_UTARA 76.89
## 3       SUMATERA_BARAT 63.70
## 4                 RIAU 80.22
## 5                JAMBI 68.42
## 6     SUMATERA_SELATAN 65.74
## 7             BENGKULU 57.97
## 8              LAMPUNG 68.78
## 9  KEP_BANGKA_BELITUNG 33.13
## 10            KEP_RIAU 59.03
## 11         DKI_JAKARTA 37.71
## 12          JAWA_BARAT 58.46
## 13         JAWA_TENGAH 74.74
## 14       DI_YOGYAKARTA 88.31
## 15          JAWA_TIMUR 76.68
## 16              BANTEN 69.14
## 17                BALI 85.73
## 18 NUSA_TENGGARA_BARAT 71.49
## 19 NUSA_TENGGARA_TIMUR 62.27
## 20    KALIMANTAN_BARAT 74.26
## 21   KALIMANTAN_TENGAH 66.44
## 22  KALIMANTAN_SELATAN 63.40
## 23    KALIMANTAN_TIMUR 76.87
## 24    KALIMANTAN_UTARA 74.86
## 25      SULAWESI_UTARA 76.84
## 26     SULAWESI_TENGAH 65.19
## 27    SULAWESI_SELATAN 78.67
## 28   SULAWESI_TENGGARA 80.11
## 29           GORONTALO 75.75
## 30      SULAWESI_BARAT 66.28
## 31              MALUKU 69.15
## 32        MALUKU_UTARA 74.49
## 33         PAPUA_BARAT 59.11
## 34    PAPUA_BARAT_DAYA 57.76
## 35               PAPUA 58.41
## 36       PAPUA_SELATAN 43.88
## 37        PAPUA_TENGAH 30.95
## 38    PAPUA_PEGUNUNGAN  9.53

length(Data$HUNI) 

## [1] 38

mean(Data$HUNI)

## [1] 65.03974

median(Data$HUNI)

## [1] 68.6

range(Data$HUNI) 

## [1]  9.53 88.31

max(Data$HUNI) -min(Data$HUNI)

## [1] 78.78

max(Data$HUNI)

## [1] 88.31

min(Data$HUNI)

## [1] 9.53

var(Data$HUNI)

## [1] 257.2884

sd(Data$HUNI)

## [1] 16.04021

quantile(Data$HUNI) 

##      0%     25%     50%     75%    100% 
##  9.5300 59.0500 68.6000 75.5275 88.3100

library(ggplot2)

ggplot(Data, aes(x ="", y = HUNI)) +
  geom_boxplot(fill = "lightcyan") +
  labs(
    title = "Box Plot Hunian Layak Indonesia 2025",
    x = "",
    y = "Hunian Layak (%)"
  ) +
  theme_minimal() +
  theme(
    plot.title = element_text(hjust = 0.5, face= "bold")
  )

library(ggplot2)

ggplot(Data, aes(x = HUNI)) +
  geom_histogram(
    binwidth = 10,
    boundary = 0,
    fill = "darkseagreen1",
    color = "black"
  ) +
  scale_x_continuous(
    breaks = seq(0,100, by = 10),
    limits = c(0, 100)
  ) +
  labs(
    title = "Persentase Hunian Layak di Indonesia Tahun 2025",
    x = "Hunian 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"
    )
  )

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  HUNI
## 1   KALIMANTAN_BARAT 74.26
## 2  KALIMANTAN_TENGAH 66.44
## 3 KALIMANTAN_SELATAN 63.40
## 4   KALIMANTAN_TIMUR 76.87
## 5   KALIMANTAN_UTARA 74.86

ggplot(Data_Kalimantan, aes(x = PROVINSI, y = HUNI, fill = PROVINSI)
       )+
  geom_col() +
  labs(
    title = "Persentase Hunian Layak Pulau Kalimantan Tahun 2025",
    x = "Provinsi",
    y = "Hunian 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"
  )