PrakKomstat_Pert2

Data <- read.table("IPM CONSOl MATERI 2 KOMSTAT.txt", header = T)
length(Data$IPM)

## [1] 38

mean(Data$IPM)

## [1] 72.38842

median(Data$IPM)

## [1] 73.18

range(Data$IPM)

## [1] 53.42 83.08

max(Data$IPM)-min(Data$IPM)

## [1] 29.66

max(Data$IPM)

## [1] 83.08

min(Data$IPM)

## [1] 53.42

var(Data$IPM)

## [1] 26.52484

sd(Data$IPM)

## [1] 5.150227

quantile(Data$IPM)

##     0%    25%    50%    75%   100% 
## 53.420 71.080 73.180 74.345 83.080

library(ggplot2)

ggplot(Data,aes(x=IPM))+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="IPM di Indonesia", 
    x="IPM",
    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 2 rows containing non-finite outside the scale range
## (`stat_bin()`).

ggplot(Data,aes(x="",y=IPM))+
  geom_boxplot(fill="red")+
  labs(title="Box Plot IPM Indonesia 2024", x="", y="IPM")+
  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   IPM
## 1   KALIMANTAN_BARAT 70.13
## 2  KALIMANTAN_TENGAH 72.73
## 3 KALIMANTAN_SELATAN 73.03
## 4   KALIMANTAN_TIMUR 78.83
## 5   KALIMANTAN_UTARA 73.02

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

# Load library
library(ggplot2)
# Baca data
data = read.table("PRODUK CONSOL MATERI 2 KOMSTAT.txt", header = T, sep = "\t")
data

##         Nama_Produk  Kategori Penjualan
## 1             Beras   Sembako        35
## 2     Minyak_Goreng   Sembako        75
## 3        Gula_Pasir   Sembako        60
## 4        Mie_Instan   Makanan       150
## 5           Biskuit   Makanan        85
## 6          Susu_UHT   Makanan        70
## 7         The_Celup   Makanan        55
## 8       Sabun_Mandi Perawatan        90
## 9             Sampo Perawatan        65
## 10       Pasta_Gigi Perawatan        70
## 11 Sabun_Cuci_ Muka Perawatan        45

# Buat barplot dengan ggplot2
ggplot(data, aes(x = Nama_Produk, y = Penjualan, fill = Kategori)) +
  geom_bar(stat = "identity") +
  labs(
    title = "Jumlah Penjualan Produk Toko MUTIA",
    x = "Produk",
    y = "Jumlah Penjualan"
  ) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    plot.title = element_text(hjust = 0.5, face = "bold")
  )# Agregasi data (total penjualan per kategori)

total_penjualan <- aggregate(Penjualan ~ Kategori, data, sum)
total_penjualan

##    Kategori Penjualan
## 1   Makanan       360
## 2 Perawatan       270
## 3   Sembako       170

# Buat barplot dengan ggplot2
ggplot(total_penjualan, aes(x = Kategori, y = Penjualan, fill = Kategori)) +
  geom_bar(stat = "identity") +
  labs(
    title = "Jumlah Penjualan per Kategori",
    x = "Kategori",
    y = "Jumlah Penjualan"
  ) +
  theme_minimal() +
  theme(
    axis.text.x = element_text(angle = 45, hjust = 1),
    plot.title = element_text(hjust = 0.5, face = "bold")
  )