.TM.Komstat2_Muhammad Ahnaf Al Fawwaz

Data<-read.table(file.choose(),header=TRUE)
Data

##                Provinsi   UHH
## 1                  ACEH 70.44
## 2        SUMATERA_UTARA 70.28
## 3        SUMATERA_BARAT 70.33
## 4                  RIAU 72.52
## 5                 JAMBI 72.04
## 6      SUMATERA_SELATAN 70.93
## 7              BENGKULU 70.13
## 8               LAMPUNG 71.50
## 9  KEP._BANGKA_BELITUNG 71.49
## 10       KEPULAUAN_RIAU 71.24
## 11          DKI_JAKARTA 73.87
## 12           JAWA_BARAT 74.07
## 13          JAWA_TENGAH 74.93
## 14       D_I_YOGYAKARTA 75.22
## 15           JAWA_TIMUR 72.35
## 16               BANTEN 71.02
## 17                 BALI 73.29
## 18  NUSA_TENGGARA_BARAT 67.73
## 19  NUSA_TENGGARA_TIMUR 67.99
## 20     KALIMANTAN_BARAT 71.55
## 21    KALIMANTAN_TENGAH 70.43
## 22   KALIMANTAN_SELATAN 69.65
## 23     KALIMANTAN_TIMUR 75.03
## 24     KALIMANTAN_UTARA 72.73
## 25       SULAWESI_UTARA 72.69
## 26      SULAWESI_TENGAH 69.42
## 27     SULAWESI_SELATAN 71.43
## 28    SULAWESI_TENGGARA 71.60
## 29            GORONTALO 69.09
## 30       SULAWESI_BARAT 66.27
## 31               MALUKU 66.99
## 32         MALUKU_UTARA 69.35
## 33          PAPUA_BARAT 67.05
## 34     PAPUA_BARAT_DAYA 67.85
## 35                PAPUA 68.79
## 36        PAPUA_SELATAN 66.45
## 37         PAPUA_TENGAH 66.99
## 38     PAPUA_PEGUNUNGAN 64.80

length(Data$UHH)

## [1] 38

mean(Data$UHH)

## [1] 70.51395

median(Data$UHH)

## [1] 70.685

range(Data$UHH)

## [1] 64.80 75.22

max(Data$UHH)-min(Data$UHH)

## [1] 10.42

max(Data$UHH)

## [1] 75.22

library(ggplot2)

ggplot(Data, aes(x = UHH)) + 
  geom_histogram(binwidth = 5, boundary = 60, fill = "Pink", color = "Black") + 
  scale_x_continuous(breaks = seq(60, 85, by = 5), limits = c(60, 85)) + 
  labs(title = "UHH di Indonesia 2024", x = "UHH", 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=UHH))+geom_boxplot(fill="red")+
         labs(title = "Box Plot UHH Indonesia 2024",x="",y="UHH")+
         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   UHH
## 1   KALIMANTAN_BARAT 71.55
## 2  KALIMANTAN_TENGAH 70.43
## 3 KALIMANTAN_SELATAN 69.65
## 4   KALIMANTAN_TIMUR 75.03
## 5   KALIMANTAN_UTARA 72.73

ggplot(Data_Kalimantan,aes(x=Provinsi,y=UHH,fill=Provinsi))+
  geom_col()+
  labs(title = "UHH Pulau Kalimantan Tahun 2024", x="provinsi",y="UHH")+
  theme_minimal()+
  theme(
    axis.text.x = element_text(angle = 10, hjust = 0.5),
    plot.title = element_text(hjust = 0.5, face = "bold"))