Test Rpubs

#Input Data

Memasukkan data ke masing-masing variabel

#Dataset
Jenis <- c("Elektronik", "Makanan/Minuman", "Makanan/Minuman", "Pakaian", "Elektronik")
ID_Barang <- c(22,13,14,5,26)
Stok <- c(30,26,21,30,17)
Harga.Ribu <- c(30,24,14,20,35)
Terjual <- c(12,32,10,24,7)
Rating <- c(5.2, 8.3, 6.0, 7.8, 9.1)

#Data Frame

Menggabungkan variabel dan membuat data frame

#Penggabungan Data
data.penjualan <- data.frame(Jenis, ID_Barang, Stok, Harga.Ribu, Terjual, Rating)
str(data.penjualan)

## 'data.frame':    5 obs. of  6 variables:
##  $ Jenis     : chr  "Elektronik" "Makanan/Minuman" "Makanan/Minuman" "Pakaian" ...
##  $ ID_Barang : num  22 13 14 5 26
##  $ Stok      : num  30 26 21 30 17
##  $ Harga.Ribu: num  30 24 14 20 35
##  $ Terjual   : num  12 32 10 24 7
##  $ Rating    : num  5.2 8.3 6 7.8 9.1

View(data.penjualan)

#Boxplot

Visualisasi data berupa boxplot

#Boxplot
library(viridis)

## Warning: package 'viridis' was built under R version 4.3.2

## Loading required package: viridisLite

num.penjualan <- data.penjualan[-1]
boxplot(num.penjualan, main="Boxplot Data Penjualan", col=viridis(5))

#Histogram

Visualisasi data berupa histogram

#Histogram
hist(num.penjualan$ID_Barang, main="Histogram ID Barang", col=viridis(7), xlab = "ID Barang", ylab="Jumlah")

#Matriks Korelasi

Menunjukkan matriks korelasi dari dataset

#Matriks Korelasi
cor(num.penjualan)

##               ID_Barang       Stok Harga.Ribu    Terjual       Rating
## ID_Barang   1.000000000 -0.5321257  0.7760551 -0.6843150 -0.009351497
## Stok       -0.532125714  1.0000000 -0.1985742  0.5494254 -0.435852972
## Harga.Ribu  0.776055123 -0.1985742  1.0000000 -0.2811527  0.340760278
## Terjual    -0.684315013  0.5494254 -0.2811527  1.0000000  0.291843540
## Rating     -0.009351497 -0.4358530  0.3407603  0.2918435  1.000000000

#Corrplot (tambahan)

Visualisasi matriks korelasi data

#Corrplot
library(corrplot)

## Warning: package 'corrplot' was built under R version 4.3.2

## corrplot 0.92 loaded

m <- cor(num.penjualan)
corrplot(m, tl.col=mako(7))

corrplot(m, method = 'shade', type='lower', order='original', col=mako(12), tl.col = viridis(8))

corrplot(m, method = 'ellipse', type='lower', order='original', addCoef.col=mako(22), tl.col = viridis(8))