UTS PDS

Bakery Synthetic Dataset

library(readxl)
data_uts <- read_excel(
  "C:/Users/acer/OneDrive/Dokumen/bakery_synthetic_dataset.xlsx",
  col_names = TRUE
)
data_uts

Ringkasan Dataset

#jelasin ini tuh dataset apa dan cantumin sumbernya

Statistika Deskriptif

Summary Data

summary(data_uts)

##       Date                         Customer_Age     Product         
##  Min.   :2023-01-01 00:00:00.00   Min.   :16.00   Length:16569      
##  1st Qu.:2023-07-06 00:00:00.00   1st Qu.:23.00   Class :character  
##  Median :2024-01-05 00:00:00.00   Median :30.00   Mode  :character  
##  Mean   :2024-01-04 00:36:45.75   Mean   :34.48                     
##  3rd Qu.:2024-07-06 00:00:00.00   3rd Qu.:44.00                     
##  Max.   :2024-12-31 00:00:00.00   Max.   :74.00                     
##    Category            Quantity       Unit_Price     Discount_Percentage
##  Length:16569       Min.   :1.000   Min.   : 24.25   Min.   : 0.000     
##  Class :character   1st Qu.:2.000   1st Qu.: 39.54   1st Qu.: 0.000     
##  Mode  :character   Median :2.000   Median : 50.81   Median : 3.800     
##                     Mean   :2.591   Mean   : 85.69   Mean   : 6.656     
##                     3rd Qu.:3.000   3rd Qu.: 71.91   3rd Qu.:10.200     
##                     Max.   :6.000   Max.   :463.49   Max.   :30.000     
##  Selling_Price      Total_Bill      Payment_Method     Stock_Available 
##  Min.   : 17.17   Min.   :  17.61   Length:16569       Min.   : 1.000  
##  1st Qu.: 36.50   1st Qu.:  74.34   Class :character   1st Qu.: 2.000  
##  Median : 48.24   Median : 119.96   Mode  :character   Median : 2.000  
##  Mean   : 79.96   Mean   : 207.86                      Mean   : 2.748  
##  3rd Qu.: 70.55   3rd Qu.: 209.11                      3rd Qu.: 3.000  
##  Max.   :463.30   Max.   :2758.98                      Max.   :21.000  
##  Units_Produced     Units_Sold       Profit        
##  Min.   : 2.000   Min.   : 1.0   Min.   :-2152.66  
##  1st Qu.: 5.000   1st Qu.: 2.0   1st Qu.:  -34.12  
##  Median : 7.000   Median : 4.0   Median :   -0.42  
##  Mean   : 7.647   Mean   : 4.9   Mean   :  -13.90  
##  3rd Qu.:10.000   3rd Qu.: 6.0   3rd Qu.:   25.14  
##  Max.   :39.000   Max.   :25.0   Max.   :  898.42

Modus Data Kategorik

modus_Product <- names(which.max(table(data_uts$Product)))
paste("Modus data kolom Product :",modus_Product)

## [1] "Modus data kolom Product : Bread"

modus_Category <- names(which.max(table(data_uts$Category)))
paste("Modus data kolom Category :",modus_Category)

## [1] "Modus data kolom Category : Beverages"

modus_Payment_Method <- names(which.max(table(data_uts$Payment_Method)))
paste("Modus data kolom Payment Method :",modus_Payment_Method)

## [1] "Modus data kolom Payment Method : UPI"

Standar Deviasi Data Numerik

sd_CustomerAge <- sd(data_uts$Customer_Age, na.rm = TRUE)
paste("Standar Deviasi data kolom Customer Age :",sd_CustomerAge)

## [1] "Standar Deviasi data kolom Customer Age : 15.2989973121483"

sd_Quantity <- sd(data_uts$Quantity, na.rm = TRUE)
paste("Standar Deviasi kolom Quantity :",sd_Quantity)

## [1] "Standar Deviasi kolom Quantity : 1.25165709836292"

sd_Unit_Price <- sd(data_uts$Unit_Price, na.rm = TRUE)
paste("Standar Deviasi kolom Unit Price :",sd_Unit_Price)

## [1] "Standar Deviasi kolom Unit Price : 96.9511935374476"

sd_DiscountPercentage <- sd(data_uts$Discount_Percentage, na.rm = TRUE)
paste("Standar Deviasi kolom Discount Percentage :",sd_DiscountPercentage)

## [1] "Standar Deviasi kolom Discount Percentage : 8.00023423563348"

sd_Selling_Price <- sd(data_uts$Selling_Price, na.rm = TRUE)
paste("Standar Deviasi kolom Selling Price :",sd_Selling_Price)

## [1] "Standar Deviasi kolom Selling Price : 91.0461599408723"

sd_Total_Bill <- sd(data_uts$Total_Bill, na.rm = TRUE)
paste("Standar Deviasi kolom Total Bill :",sd_Total_Bill)

## [1] "Standar Deviasi kolom Total Bill : 281.230169963612"

sd_Stock_Available <- sd(data_uts$Stock_Available, na.rm = TRUE)
paste("Standar Deviasi kolom stock Available :",sd_Stock_Available)

## [1] "Standar Deviasi kolom stock Available : 1.9003413356256"

sd_Units_Produced <- sd(data_uts$Units_Produced, na.rm = TRUE)
paste("Standar Deviasi kolom Units Produced :",sd_Units_Produced)

## [1] "Standar Deviasi kolom Units Produced : 4.43546590326741"

sd_Units_Sold <- sd(data_uts$Units_Sold, na.rm = TRUE)
paste("Standar Deviasi kolom Units Sold :",sd_Units_Sold)

## [1] "Standar Deviasi kolom Units Sold : 3.33244234115362"

sd_Profit <- sd(data_uts$Profit, na.rm = TRUE)
paste("Standar Deviasi kolom Profit :",sd_Profit)

## [1] "Standar Deviasi kolom Profit : 109.335028153946"

Ringkasan Statistika Deskriptif Data

 #penjelasan stat deskriptifnya nnah kan itu ada 13 kategori nanti masing" orang dibagi 4 4 aja buat penjelasan stat deskriptifnya