TM

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

##                     Provinsi  TPT
## 1                       ACEH 5.88
## 2             SUMATERA UTARA 5.01
## 3             SUMATERA BARAT 5.51
## 4                       RIAU 4.09
## 5                      JAMBI 3.99
## 6           SUMATERA SELATAN 3.59
## 7                   BENGKULU 3.23
## 8                    LAMPUNG 3.95
## 9  KEPULAUAN BANGKA BELITUNG 4.15
## 10            KEPULAUAN RIAU 6.87
## 11               DKI JAKARTA 6.03
## 12                JAWA BARAT 6.64
## 13               JAWA TENGAH 4.24
## 14             DI YOGYAKARTA 3.05
## 15                JAWA TIMUR 3.55
## 16                    BANTEN 6.59
## 17                      BALI 1.59
## 18       NUSA TENGGARA BARAT 2.99
## 19       NUSA TENGGARA TIMUR 3.16
## 20          KALIMANTAN BARAT 4.57
## 21         KALIMANTAN TENGAH 3.44
## 22        KALIMANTAN SELATAN 3.80
## 23          KALIMANTAN TIMUR 5.27
## 24          KALIMANTAN UTARA 3.90
## 25            SULAWESI UTARA 5.75
## 26           SULAWESI TENGAH 2.95
## 27          SULAWESI SELATAN 4.95
## 28         SULAWESI TENGGARA 3.25
## 29                 GORONTALO 3.17
## 30            SULAWESI BARAT 2.93
## 31                    MALUKU 5.80
## 32              MALUKU UTARA 4.46
## 33               PAPUA BARAT 4.10
## 34          PAPUA BARAT DAYA 6.41
## 35                     PAPUA 7.02
## 36             PAPUA SELATAN 5.25
## 37              PAPUA TENGAH 3.83
## 38          PAPUA PEGUNUNGAN 1.70

# Perhitungan Statistika Deskriptif
length(Data$TPT)

## [1] 38

mean(Data$TPT)

## [1] 4.385789

median(Data$TPT)

## [1] 4.095

range(Data$TPT)

## [1] 1.59 7.02

max(Data$TPT) - min(Data$TPT)

## [1] 5.43

max(Data$TPT)

## [1] 7.02

min(Data$TPT)

## [1] 1.59

var(Data$TPT)

## [1] 1.938966

sd(Data$TPT)

## [1] 1.392467

quantile(Data$TPT)

##     0%    25%    50%    75%   100% 
## 1.5900 3.2975 4.0950 5.4500 7.0200

summary(Data$TPT)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   1.590   3.297   4.095   4.386   5.450   7.020

#Histogram
library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.5.2

ggplot(Data, aes(x = TPT)) +
  geom_histogram(
    binwidth = 1,
    boundary = 1,
    fill = "skyblue",
    color = "black"
  ) +
  scale_x_continuous(
    breaks = seq(1, 8, by = 1),
    limits = c(1, 8)
  ) +
  labs(
    title = "Histogram Tingkat Pengangguran Terbuka (TPT) Indonesia 2026",
    x = "TPT (%)",
    y = "Frekuensi"
  ) +
  theme_classic() +
  theme(
    axis.text.x = element_text(angle = 0, hjust = 0.5),
    plot.title = element_text(hjust = 0.5, face = "bold")
  )

#Boxplot
library(ggplot2)
ggplot(Data, aes(x = "", y = TPT)) +
  geom_boxplot(fill = "lightgreen", color = "darkgreen") +
  labs(
    title = "Box Plot TPT Indonesia 2026",
    x = "",
    y = "TPT (%)"
  ) +
  theme_minimal() +
  theme(
    plot.title = element_text(hjust = 0.5, face = "bold")
  )

#Visualisasi Data Khusus Pulau Kalimantan
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  TPT
## 1   KALIMANTAN BARAT 4.57
## 2  KALIMANTAN TENGAH 3.44
## 3 KALIMANTAN SELATAN 3.80
## 4   KALIMANTAN TIMUR 5.27
## 5   KALIMANTAN UTARA 3.90

ggplot(Data_Kalimantan, aes(x = Provinsi, y = TPT, fill = Provinsi)) +
  geom_col() +
  labs(
    title = "Tingkat Pengangguran Terbuka (TPT) Pulau Kalimantan Tahun 2026",
    x = "Provinsi",
    y = "TPT (%)"
  ) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    plot.title = element_text(hjust = 0.5, face = "bold"),
    legend.position = "none"
  )