tugas week 5

# Contoh data (silakan ganti dengan data kamu)
data <- data.frame(
  Pelanggan = c("Ahmad", "Beni", "Chelsea", "Ahmad", "Beni", "Dimas", "Ahmad"),
  Total_Belanja = c(6000000, 4000000, 7000000, 8000000, 9000000, 3000000, 10000000)
)

# Filter hanya transaksi dengan belanja > 5.000.000
data_filter <- subset(data, Total_Belanja > 5000000)

# Hitung frekuensi belanja per pelanggan
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

hasil <- data_filter %>%
  group_by(Pelanggan) %>%
  summarise(Jumlah_Transaksi = n()) %>%
  arrange(desc(Jumlah_Transaksi))

# Tampilkan pelanggan yang paling sering belanja > 5 juta
hasil

## # A tibble: 3 × 2
##   Pelanggan Jumlah_Transaksi
##   <chr>                <int>
## 1 Ahmad                    3
## 2 Beni                     1
## 3 Chelsea                  1

data <- data.frame(
  Pelanggan = c("Ahmad","Beni","Chelsea","Ahmad","Dimas","Ahmad","Chelsea","Beni","Chelsea","Ahmad"),
  Penghasilan = c(6000000,4000000,7000000,6000000,8000000,
                  6000000,7000000,4000000,7000000,6000000)
)

library(dplyr)

hasil <- data %>%
  filter(Penghasilan > 5000000) %>%
  count(Pelanggan, sort = TRUE)

head(hasil, 1)

##   Pelanggan n
## 1     Ahmad 4

# Data contoh
data <- data.frame(
  Pelanggan = c("Ahmad","Beni","Chelsea","Ahmad","Dimas","Ahmad","Chelsea","Beni","Chelsea","Ahmad"),
  Penghasilan = c(6000000,4000000,7000000,6000000,8000000,
                  6000000,7000000,4000000,7000000,6000000)
)

# Filter hanya penghasilan > 5 juta
data_filter <- data[data$Penghasilan > 5000000, ]

# Hitung siapa yang paling sering
tab <- table(data_filter$Pelanggan)
top_pelanggan <- names(which.max(tab))

cat("Pelanggan yang paling sering membeli dengan penghasilan > 5 juta adalah:",
    top_pelanggan, "dengan", max(tab), "kali transaksi\n")

## Pelanggan yang paling sering membeli dengan penghasilan > 5 juta adalah: Ahmad dengan 4 kali transaksi

# Contoh data
data <- data.frame(
  Pelanggan = c("Ahmad","Beni","Chelsea","Dimas","Maryam","Rahmat"),
  Jenis_Kelamin = c("L","L","P","L","P","L"),
  Tempat_Tinggal = c("Kota","Desa","Desa","Desa","Kota","Desa"),
  Total_Belanja = c(4000000,6000000,7000000,3000000,9000000,8000000)
)

# Filter: tinggal di desa & belanja > 5 juta
data_filter <- subset(data, Tempat_Tinggal == "Desa" & Total_Belanja > 5000000)

# Ambil jenis kelamin pelanggan
print(data_filter[, c("Pelanggan","Jenis_Kelamin","Total_Belanja")])

##   Pelanggan Jenis_Kelamin Total_Belanja
## 2      Beni             L         6e+06
## 3   Chelsea             P         7e+06
## 6    Rahmat             L         8e+06

# Contoh data
data <- data.frame(
  Pelanggan = c("Ahmad","Beni","Chelsea","Dimas","Maryam","Rahmat"),
  Jenis_Kelamin = c("L","L","P","L","P","L"),
  Tempat_Tinggal = c("Kota","Desa","Desa","Desa","Kota","Desa"),
  Total_Belanja = c(4000000,6000000,7000000,3000000,9000000,8000000),
  Penghasilan = c(7000000,8000000,6500000,5000000,10000000,9000000)
)

# Filter: tinggal di desa & belanja > 5 juta
data_filter <- subset(data, Tempat_Tinggal == "Desa" & Total_Belanja > 5000000)

# Tampilkan nama, penghasilan, dan total belanja
print(data_filter[, c("Pelanggan","Penghasilan","Total_Belanja")])

##   Pelanggan Penghasilan Total_Belanja
## 2      Beni     8000000         6e+06
## 3   Chelsea     6500000         7e+06
## 6    Rahmat     9000000         8e+06