Analisis Efisiensi Profit pada kopi
M. Arka Sena
2026-04-17
DESKRIPSI INSIGHT
Analisis ini bertujuan untuk mengkaji efisiensi profit pada Coffee Chain Dataset. Efisiensi profit diukur perbandingan antara profit dan total expenses.
Berbeda dengan analisis profit biasa, pendekatan ini tidak hanya melihat besarnya keuntungan, tetapi juga mempertimbangkan seberapa efisien biaya yang dikeluarkan untuk menghasilkan profit.
Variabel yang digunakan: - Profit - Total Expenses - Product Type - Market
Tujuan analisis adalah untuk mengetahui perbedaan efisiensi antar jenis produk dan market.
IMPORT DATA
library(readxl)
data <- read_excel("D:/SIM/1. Tugas SIM 2025B - Coffee Chain Datasets.xlsx")
head(data)## # A tibble: 6 × 20
## `Area Code` Date Market `Market Size` Product `Product Line`
## <dbl> <dttm> <chr> <chr> <chr> <chr>
## 1 719 2012-01-01 00:00:00 Central Major Market Amaretto Beans
## 2 970 2012-01-01 00:00:00 Central Major Market Colombian Beans
## 3 970 2012-01-01 00:00:00 Central Major Market Decaf Ir… Beans
## 4 303 2012-01-01 00:00:00 Central Major Market Green Tea Leaves
## 5 303 2012-01-01 00:00:00 Central Major Market Caffe Mo… Beans
## 6 720 2012-01-01 00:00:00 Central Major Market Decaf Es… Beans
## # ℹ 14 more variables: `Product Type` <chr>, State <chr>, Type <chr>,
## # `Budget COGS` <dbl>, `Budget Margin` <dbl>, `Budget Profit` <dbl>,
## # `Budget Sales` <dbl>, COGS <dbl>, Inventory <dbl>, Margin <dbl>,
## # Marketing <dbl>, Profit <dbl>, Sales <dbl>, `Total Expenses` <dbl>str(data)## tibble [4,248 × 20] (S3: tbl_df/tbl/data.frame)
## $ Area Code : num [1:4248] 719 970 970 303 303 720 970 719 970 719 ...
## $ Date : POSIXct[1:4248], format: "2012-01-01" "2012-01-01" ...
## $ Market : chr [1:4248] "Central" "Central" "Central" "Central" ...
## $ Market Size : chr [1:4248] "Major Market" "Major Market" "Major Market" "Major Market" ...
## $ Product : chr [1:4248] "Amaretto" "Colombian" "Decaf Irish Cream" "Green Tea" ...
## $ Product Line : chr [1:4248] "Beans" "Beans" "Beans" "Leaves" ...
## $ Product Type : chr [1:4248] "Coffee" "Coffee" "Coffee" "Tea" ...
## $ State : chr [1:4248] "Colorado" "Colorado" "Colorado" "Colorado" ...
## $ Type : chr [1:4248] "Regular" "Regular" "Decaf" "Regular" ...
## $ Budget COGS : num [1:4248] 90 80 100 30 60 80 140 50 50 40 ...
## $ Budget Margin : num [1:4248] 130 110 140 50 90 130 160 80 70 70 ...
## $ Budget Profit : num [1:4248] 100 80 110 30 70 80 110 20 40 20 ...
## $ Budget Sales : num [1:4248] 220 190 240 80 150 210 300 130 120 110 ...
## $ COGS : num [1:4248] 89 83 95 44 54 72 170 63 60 58 ...
## $ Inventory : num [1:4248] 777 623 821 623 456 ...
## $ Margin : num [1:4248] 130 107 139 56 80 108 171 87 80 72 ...
## $ Marketing : num [1:4248] 24 27 26 14 15 23 47 57 19 22 ...
## $ Profit : num [1:4248] 94 68 101 30 54 53 99 0 33 17 ...
## $ Sales : num [1:4248] 219 190 234 100 134 180 341 150 140 130 ...
## $ Total Expenses: num [1:4248] 36 39 38 26 26 55 72 87 47 55 ...summary(data)## Area Code Date Market
## Min. :203.0 Min. :2012-01-01 00:00:00 Length:4248
## 1st Qu.:417.0 1st Qu.:2012-06-23 12:00:00 Class :character
## Median :573.0 Median :2012-12-16 12:00:00 Mode :character
## Mean :582.3 Mean :2012-12-15 22:00:00
## 3rd Qu.:772.0 3rd Qu.:2013-06-08 12:00:00
## Max. :985.0 Max. :2013-12-01 00:00:00
## Market Size Product Product Line Product Type
## Length:4248 Length:4248 Length:4248 Length:4248
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## State Type Budget COGS Budget Margin
## Length:4248 Length:4248 Min. : 0.00 Min. :-210.0
## Class :character Class :character 1st Qu.: 30.00 1st Qu.: 50.0
## Mode :character Mode :character Median : 50.00 Median : 70.0
## Mean : 74.83 Mean : 100.8
## 3rd Qu.: 90.00 3rd Qu.: 130.0
## Max. :450.00 Max. : 690.0
## Budget Profit Budget Sales COGS Inventory
## Min. :-320.00 Min. : 0.0 Min. : 0.00 Min. :-3534.0
## 1st Qu.: 20.00 1st Qu.: 80.0 1st Qu.: 43.00 1st Qu.: 432.0
## Median : 40.00 Median : 130.0 Median : 60.00 Median : 619.0
## Mean : 60.91 Mean : 175.6 Mean : 84.43 Mean : 749.4
## 3rd Qu.: 80.00 3rd Qu.: 210.0 3rd Qu.:100.00 3rd Qu.: 910.5
## Max. : 560.00 Max. :1140.0 Max. :364.00 Max. : 8252.0
## Margin Marketing Profit Sales
## Min. :-302.00 Min. : 0.00 Min. :-638.0 Min. : 17
## 1st Qu.: 52.75 1st Qu.: 13.00 1st Qu.: 17.0 1st Qu.:100
## Median : 76.00 Median : 22.00 Median : 40.0 Median :138
## Mean : 104.29 Mean : 31.19 Mean : 61.1 Mean :193
## 3rd Qu.: 132.00 3rd Qu.: 39.00 3rd Qu.: 92.0 3rd Qu.:230
## Max. : 613.00 Max. :156.00 Max. : 778.0 Max. :912
## Total Expenses
## Min. : 10.00
## 1st Qu.: 33.00
## Median : 46.00
## Mean : 54.06
## 3rd Qu.: 65.00
## Max. :190.00DATA PREPROCESSING (BUAT VARIABEL BARU)
data$Efficiency <- data$Profit / data$`Total Expenses`VISUALISASI DATA
Efisiensi per Product Type
library(ggplot2)
ggplot(data, aes(x = `Product Type`, y = Efficiency)) +
geom_boxplot(fill = "skyblue") +
labs(title = "Efisiensi Profit per Jenis Produk",
x = "Product Type",
y = "Efficiency")
Efisiensi per Market
ggplot(data, aes(x = Market, y = Efficiency)) +
geom_boxplot(fill = "orange") +
labs(title = "Efisiensi Profit per Market",
x = "Market",
y = "Efficiency")
ANALISIS STATISTIK (ANOVA)
anova_model <- aov(Efficiency ~ `Product Type`, data = data)
summary(anova_model)## Df Sum Sq Mean Sq F value Pr(>F)
## `Product Type` 3 19 6.345 3.159 0.0237 *
## Residuals 4244 8524 2.009
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1ANALISIS TAMBAHAN
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, uniondata %>%
group_by(Market, `Product Type`) %>%
summarise(avg_eff = mean(Efficiency, na.rm = TRUE)) %>%
arrange(desc(avg_eff))## `summarise()` has grouped output by 'Market'. You can override using the
## `.groups` argument.## # A tibble: 15 × 3
## # Groups: Market [4]
## Market `Product Type` avg_eff
## <chr> <chr> <dbl>
## 1 East Coffee 2.83
## 2 East Tea 2.22
## 3 Central Espresso 1.78
## 4 West Herbal Tea 1.57
## 5 Central Herbal Tea 1.55
## 6 South Coffee 1.52
## 7 West Espresso 1.42
## 8 South Espresso 1.25
## 9 Central Coffee 1.24
## 10 Central Tea 1.11
## 11 West Tea 1.06
## 12 South Herbal Tea 0.745
## 13 East Herbal Tea 0.535
## 14 East Espresso 0.510
## 15 West Coffee 0.373INTERPRETASI HASIL
Interpretasi
Berdasarkan hasil analisis, efisiensi profit berbeda-beda antar jenis produk.
Beberapa produk memiliki rasio profit terhadap biaya yang lebih tinggi, yang menunjukkan bahwa produk tersebut lebih efisien dalam menghasilkan keuntungan.
Selain itu, terdapat variasi efisiensi antar market, yang menunjukkan bahwa strategi operasional dan biaya di setiap wilayah berbeda.
Hasil ANOVA menunjukkan bahwa terdapat perbedaan signifikan efisiensi antar jenis produk, sehingga jenis produk menjadi faktor penting dalam menentukan efisiensi profit.
Analisis tambahan menunjukkan kombinasi market dan product type yang paling efisien, yang dapat dijadikan acuan dalam pengambilan keputusan bisnis.
Dengan demikian, perusahaan sebaiknya tidak hanya fokus pada peningkatan profit, tetapi juga pada efisiensi penggunaan biaya.