tm2komstat

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

##                Provinsi   APS
## 1                  ACEH 34.95
## 2        SUMATERA_UTARA 30.48
## 3        SUMATERA_BARAT 38.84
## 4                  RIAU 33.03
## 5                 JAMBI 25.23
## 6      SUMATERA_SELATAN 21.24
## 7              BENGKULU 34.18
## 8               LAMPUNG 20.68
## 9  KEP._BANGKA_BELITUNG 21.13
## 10            KEP._RIAU 26.61
## 11          DKI_JAKARTA 34.21
## 12           JAWA_BARAT 27.98
## 13          JAWA_TENGAH 27.44
## 14        DI_YOGYAKARTA 54.72
## 15           JAWA_TIMUR 28.90
## 16               BANTEN 24.45
## 17                 BALI 34.32
## 18  NUSA_TENGGARA_BARAT 28.88
## 19  NUSA_TENGGARA_TIMUR 31.41
## 20     KALIMANTAN_BARAT 26.84
## 21    KALIMANTAN_TENGAH 24.91
## 22   KALIMANTAN_SELATAN 30.91
## 23     KALIMANTAN_TIMUR 33.15
## 24     KALIMANTAN_UTARA 29.25
## 25       SULAWESI_UTARA 25.57
## 26      SULAWESI_TENGAH 26.50
## 27     SULAWESI_SELATAN 33.80
## 28    SULAWESI_TENGGARA 33.67
## 29            GORONTALO 35.02
## 30       SULAWESI_BARAT 23.55
## 31               MALUKU 29.66
## 32         MALUKU_UTARA 25.38
## 33          PAPUA_BARAT 34.53
## 34     PAPUA_BARAT_DAYA 35.19
## 35                PAPUA 38.16
## 36        PAPUA_SELATAN 27.57
## 37         PAPUA_TENGAH 15.48
## 38     PAPUA_PEGUNUNGAN 12.48

length(Data$APS)

## [1] 38

mean(Data$APS)

## [1] 29.48158

median(Data$APS)

## [1] 29.075

range(Data$APS)

## [1] 12.48 54.72

max(Data$APS)-min(Data$APS)

## [1] 42.24

max(Data$APS)

## [1] 54.72

min(Data$APS)

## [1] 12.48

var(Data$APS)

## [1] 51.95072

sd(Data$APS)

## [1] 7.207685

quantile(Data$APS)

##      0%     25%     50%     75%    100% 
## 12.4800 25.4275 29.0750 34.0850 54.7200

library(ggplot2)

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

ggplot(Data, aes(x = APS)) +
  geom_histogram(
    binwidth = 5,
    boundary = 10,
    fill = "lightblue",
    color = "black"
  ) +
  scale_x_continuous(
    breaks = seq(10, 55, by = 5),
    limits = c(10, 55)
  ) +
  labs(
    title = "APS Usia 19-23 Tahun di Indonesia 2025",
    x = "APS (%)",
    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 = APS)) +
  geom_boxplot(fill = "yellow") +
  labs(
    title = "Box Plot APS Usia 19-23 Tahun di Indonesia 2025",
    x = "",
    y = "APS (%)"
  ) +
  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 '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   APS
## 1   KALIMANTAN_BARAT 26.84
## 2  KALIMANTAN_TENGAH 24.91
## 3 KALIMANTAN_SELATAN 30.91
## 4   KALIMANTAN_TIMUR 33.15
## 5   KALIMANTAN_UTARA 29.25

ggplot(Data_Kalimantan, aes(
  x = Provinsi,
  y = APS,
  fill = Provinsi
)) +
  geom_col() +
  labs(
    title = "APS Usia 19-23 Tahun Pulau Kalimantan 2025",
    x = "Provinsi",
    y = "APS (%)"
  ) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    plot.title = element_text(
      hjust = 0.5,
      face = "bold"
    ),
    legend.position = "none"
  )