# Memuat paket yang diperlukan untuk koneksi database dan visualisasi
library(DBI)
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.5.2
library(scales)
## Warning: package 'scales' was built under R version 4.5.2

Pendahuluan

Laporan ini menyajikan banyaknya item untuk tiap product scale dari database “classicmodels”. Proses ini mengintegrasikan SQL untuk pengambilan data dan R untuk visualisasi. # Koneksi Database dan Pengambilan Data Langkah pertama adalah membangun koneksi antara RStudio dan database MySQL menggunakan fungsi dbConnect()

con <- DBI::dbConnect(odbc::odbc(),
Driver = "MySQL ODBC 8.0 ANSI Driver",
Server = "127.0.0.1",
Database = "classicmodels",
UID = "root",
PWD = "1strinyaWOOSEOK", #sesuaikan dg password masing-masing
Port = 3306)

Setelah koneksi terjalin, kita menggunakan blok kode SQL untuk mendapatkan nilai pesanan yang diterima dari pelanggan di negara-negara nordic. Simpan data hasil kueri data dalam suatu data frame R.

# Mendapatkan data yang diperlukan

data1 <- dbGetQuery(con, "select o.orderNumber, country, sum(quantityordered*priceeach) as total_value 
from orders o join Orderdetails od on o.OrderNumber=od.OrderNumber
join customers c on c.customerNumber= o.customerNumber
where country in ('Denmark', 'Finland', 'Norway', 'Sweden')
group by o.orderNumber")
data1
##    orderNumber  country total_value
## 1        10103   Norway    50218.95
## 2        10105  Denmark    53959.21
## 3        10112   Sweden     7674.94
## 4        10141  Finland    29716.86
## 5        10151  Finland    32723.04
## 6        10155  Finland    37602.48
## 7        10158   Norway     1491.38
## 8        10161  Denmark    36164.46
## 9        10167   Sweden    44167.09
## 10       10181 Norway      55069.55
## 11       10188 Norway      29954.91
## 12       10238  Denmark    28211.70
## 13       10239  Finland    16212.59
## 14       10247  Finland    28394.54
## 15       10256  Denmark     4710.73
## 16       10284 Norway      32260.16
## 17       10289 Norway      12538.01
## 18       10291   Sweden    48809.90
## 19       10299  Finland    34341.08
## 20       10301 Norway      36798.88
## 21       10309   Norway    17876.32
## 22       10314  Denmark    53745.34
## 23       10320   Sweden    16799.03
## 24       10325   Norway    34638.14
## 25       10326   Sweden    19206.68
## 26       10327  Denmark    20564.86
## 27       10334   Sweden    23014.17
## 28       10363  Finland    45785.34
## 29       10373  Finland    46770.52
## 30       10377  Finland    23602.90
## 31       10389   Sweden    27966.54
## 32       10406  Denmark    21638.62

Visualisasi histogram nilai pesanan

Kita menggunakan library ggplot2 untuk membuat barchart. Fungsi geom_his() digunakan untuk melihat banyaknya distribusi dari frekkuansi nilai pesanan tiap product scale.

# Membuat histogram nilai pesanan
ggplot(data1, aes(x = total_value)) +
geom_histogram(aes(fill = "pink")) +
theme_minimal() +
labs(title = "Distribusi Nilai Pesanan di Negara Nordic",
        x = "Nilai Pesanan (USD)",
        y = "Frekuensi (Banyakya Pesanan")
## `stat_bin()` using `bins = 30`. Pick better value `binwidth`.

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