Pertemuan 3 SIM
Alifia Oktaviani
2026-03-11
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library(DBI)## Warning: package 'DBI' was built under R version 4.4.2library(ggplot2)## Warning: package 'ggplot2' was built under R version 4.4.2library(scales)## Warning: package 'scales' was built under R version 4.4.2con2 <- DBI::dbConnect(odbc::odbc(),
Driver = "MySQL ODBC 8.0 ANSI Driver",
Server = "127.0.0.1",
Database = "classicmodels",
UID = "root",
PWD = "fiaokta2",
Port = 3306)# Histogram nilai orders dari negara Nordic
query3 <- "SELECT c.country, (od.quantityOrdered * od.priceEach) AS value
FROM customers c
JOIN orders o ON c.customerNumber = o.customerNumber
JOIN orderdetails od ON o.orderNumber = od.orderNumber
WHERE c.country IN ('Denmark','Finland','Norway','Sweden')"
query3## [1] "SELECT c.country, (od.quantityOrdered * od.priceEach) AS value\nFROM customers c\nJOIN orders o ON c.customerNumber = o.customerNumber\nJOIN orderdetails od ON o.orderNumber = od.orderNumber\nWHERE c.country IN ('Denmark','Finland','Norway','Sweden')"data3 <- dbGetQuery(con2, query3)
data3## country value
## 1 Norway 5571.80
## 2 Norway 5026.14
## 3 Norway 3284.28
## 4 Norway 3307.50
## 5 Norway 1283.48
## 6 Norway 2489.13
## 7 Norway 2164.40
## 8 Norway 2173.00
## 9 Norway 3970.26
## 10 Norway 3530.52
## 11 Norway 1670.75
## 12 Norway 3864.24
## 13 Norway 2215.50
## 14 Norway 2866.26
## 15 Norway 2850.75
## 16 Norway 3950.94
## 17 Norway 1491.38
## 18 Norway 3884.34
## 19 Norway 3759.60
## 20 Norway 2035.32
## 21 Norway 1429.44
## 22 Norway 4694.50
## 23 Norway 2073.12
## 24 Norway 5241.44
## 25 Norway 8116.50
## 26 Norway 3986.40
## 27 Norway 2753.76
## 28 Norway 5048.12
## 29 Norway 1686.06
## 30 Norway 1548.40
## 31 Norway 3782.90
## 32 Norway 2474.56
## 33 Sweden 5717.64
## 34 Sweden 1957.30
## 35 Sweden 5730.04
## 36 Sweden 3575.95
## 37 Sweden 2425.92
## 38 Sweden 3491.00
## 39 Sweden 1576.12
## 40 Sweden 3033.28
## 41 Sweden 3686.50
## 42 Sweden 4937.63
## 43 Sweden 3556.34
## 44 Sweden 1626.80
## 45 Sweden 2366.13
## 46 Sweden 3380.26
## 47 Sweden 4968.00
## 48 Sweden 1797.58
## 49 Sweden 2946.60
## 50 Sweden 4983.79
## 51 Sweden 4937.94
## 52 Denmark 6392.00
## 53 Denmark 8434.52
## 54 Denmark 4114.52
## 55 Denmark 3004.98
## 56 Denmark 3333.74
## 57 Denmark 3094.68
## 58 Denmark 5072.71
## 59 Denmark 3232.24
## 60 Denmark 3773.50
## 61 Denmark 2214.00
## 62 Denmark 2511.69
## 63 Denmark 1882.32
## 64 Denmark 3594.24
## 65 Denmark 2184.82
## 66 Denmark 1119.25
## 67 Denmark 4521.72
## 68 Denmark 3031.08
## 69 Denmark 1468.40
## 70 Denmark 2802.35
## 71 Denmark 7058.45
## 72 Denmark 5303.32
## 73 Denmark 2532.36
## 74 Denmark 1494.02
## 75 Denmark 3178.66
## 76 Denmark 1532.07
## 77 Denmark 3863.50
## 78 Denmark 3345.30
## 79 Denmark 1871.00
## 80 Denmark 1593.60
## 81 Denmark 1366.05
## 82 Denmark 3661.02
## 83 Denmark 3086.54
## 84 Denmark 1777.85
## 85 Denmark 7598.16
## 86 Denmark 6418.56
## 87 Denmark 7621.90
## 88 Norway 4202.82
## 89 Norway 3189.76
## 90 Norway 1340.60
## 91 Norway 3855.60
## 92 Norway 5480.64
## 93 Norway 5226.48
## 94 Norway 1643.18
## 95 Norway 2718.45
## 96 Norway 3528.36
## 97 Norway 6629.85
## 98 Norway 2195.10
## 99 Norway 2651.66
## 100 Norway 5344.56
## 101 Norway 1539.52
## 102 Norway 1215.45
## 103 Norway 1253.27
## 104 Norway 3054.25
## 105 Norway 4593.60
## 106 Norway 4248.40
## 107 Norway 8191.80
## 108 Norway 1666.88
## 109 Norway 2395.00
## 110 Norway 2468.00
## 111 Norway 3604.04
## 112 Norway 2787.19
## 113 Norway 3513.86
## 114 Norway 1074.00
## 115 Norway 6095.25
## 116 Norway 1854.90
## 117 Finland 4134.40
## 118 Finland 5273.26
## 119 Finland 3671.36
## 120 Finland 3070.23
## 121 Finland 1433.82
## 122 Finland 1922.70
## 123 Finland 2823.47
## 124 Finland 2582.36
## 125 Finland 2867.52
## 126 Finland 1755.00
## 127 Finland 3302.40
## 128 Finland 3094.52
## 129 Finland 1671.44
## 130 Finland 1760.88
## 131 Finland 4773.69
## 132 Finland 2964.24
## 133 Finland 2424.63
## 134 Finland 5832.96
## 135 Finland 5032.29
## 136 Finland 1942.71
## 137 Finland 2121.28
## 138 Finland 869.04
## 139 Finland 3218.60
## 140 Finland 3400.76
## 141 Finland 1570.56
## 142 Finland 5643.00
## 143 Finland 4359.60
## 144 Finland 1909.60
## 145 Finland 4506.48
## 146 Finland 5613.66
## 147 Denmark 3408.16
## 148 Denmark 4387.72
## 149 Denmark 6691.68
## 150 Denmark 2884.20
## 151 Denmark 4780.80
## 152 Denmark 1568.00
## 153 Denmark 2719.13
## 154 Denmark 1087.67
## 155 Denmark 1653.80
## 156 Denmark 2701.00
## 157 Denmark 1455.40
## 158 Denmark 2826.90
## 159 Denmark 6711.94
## 160 Denmark 5768.40
## 161 Denmark 6104.16
## 162 Denmark 4319.55
## 163 Denmark 5707.80
## 164 Denmark 2595.20
## 165 Denmark 1948.33
## 166 Denmark 3748.54
## 167 Denmark 2263.36
## 168 Denmark 1240.98
## 169 Denmark 4224.84
## 170 Denmark 2044.35
## 171 Denmark 3241.00
## 172 Denmark 1914.44
## 173 Denmark 1912.45
## 174 Norway 6173.55
## 175 Norway 2121.33
## 176 Norway 2238.72
## 177 Norway 1952.40
## 178 Norway 2333.37
## 179 Norway 1375.71
## 180 Norway 1399.65
## 181 Norway 3027.00
## 182 Norway 1180.74
## 183 Norway 2104.56
## 184 Norway 4307.85
## 185 Norway 1700.00
## 186 Norway 2345.28
## 187 Norway 4242.05
## 188 Norway 3783.04
## 189 Norway 5616.03
## 190 Norway 2497.44
## 191 Norway 3115.81
## 192 Norway 5344.56
## 193 Norway 1746.09
## 194 Norway 896.50
## 195 Norway 1540.80
## 196 Norway 1908.06
## 197 Norway 6108.50
## 198 Finland 2758.80
## 199 Finland 6547.61
## 200 Finland 5232.22
## 201 Finland 2275.26
## 202 Finland 3520.65
## 203 Finland 4615.80
## 204 Finland 880.50
## 205 Finland 2288.25
## 206 Finland 1774.89
## 207 Finland 2829.06
## 208 Finland 2103.99
## 209 Finland 3223.22
## 210 Finland 6367.09
## 211 Finland 649.40
## 212 Finland 3868.89
## 213 Finland 4614.48
## 214 Finland 4018.00
## 215 Finland 1665.40
## 216 Finland 4976.00
## 217 Finland 2238.96
## 218 Finland 2716.23
## 219 Finland 2480.32
## 220 Finland 1928.78
## 221 Finland 2421.90
## 222 Finland 2552.00
## 223 Finland 2462.08
## 224 Finland 2844.99
## 225 Finland 3201.44
## 226 Finland 3086.54
## 227 Finland 3064.95
## 228 Finland 1105.00
## 229 Finland 1393.45
## 230 Finland 2413.95
## 231 Finland 6257.94
## 232 Finland 4845.23
## 233 Finland 4893.96
## 234 Finland 1017.20
## 235 Finland 675.78
## 236 Finland 4163.60
## 237 Finland 1272.72
## 238 Finland 4176.48
## 239 Finland 8594.52
## 240 Finland 3512.50
## 241 Finland 4531.41
## 242 Finland 6893.76
## 243 Finland 2336.40
## 244 Finland 2525.95
## 245 Finland 5971.35
## 246 Finland 3633.58
## 247 Finland 2333.42
## 248 Finland 4767.44
## 249 Finland 1355.20
## 250 Finland 3180.90
## 251 Finland 2998.56
## 252 Finland 1671.04
## 253 Finland 3458.00
## 254 Finland 1471.68
## 255 Finland 2412.30
## 256 Finland 1093.05
## 257 Finland 3526.25
## 258 Finland 3267.57
## 259 Finland 4645.00
## 260 Sweden 5445.44
## 261 Sweden 6102.56
## 262 Sweden 3205.28
## 263 Sweden 2879.80
## 264 Sweden 3649.80
## 265 Sweden 1151.01
## 266 Sweden 1540.00
## 267 Sweden 2062.08
## 268 Sweden 2140.20
## 269 Sweden 2838.00
## 270 Sweden 2546.20
## 271 Sweden 2859.36
## 272 Sweden 2043.36
## 273 Sweden 2335.76
## 274 Sweden 1708.40
## 275 Sweden 1659.84
## 276 Sweden 7770.37
## 277 Sweden 4254.90
## 278 Sweden 5043.00
## 279 Sweden 3970.44
## 280 Sweden 1358.76
## 281 Sweden 4666.16
## 282 Sweden 2079.77
## 283 Sweden 2143.60
## 284 Sweden 4649.28
## 285 Sweden 1313.12
## 286 Sweden 5275.20
## 287 Sweden 2153.58
## 288 Sweden 1696.00
## 289 Sweden 2435.72
## 290 Sweden 4755.40
## 291 Sweden 2378.25
## 292 Sweden 2757.96
## 293 Sweden 4817.03
## 294 Sweden 3131.59
## 295 Sweden 2031.51
## 296 Sweden 5071.50
## 297 Sweden 3023.30ggplot(data3, aes(x = value)) +
geom_histogram(binwidth = 1000, fill = "purple", color = "black", alpha = 0.8) +
theme_minimal() +
labs(title = "Histogram Nilai Orders dari Negara Nordic",
x = "Nilai Orders (USD)",
y = "Frekuensi") +
scale_x_continuous(labels = scales::comma)
# Heatmap product line dan kota di Norway
query4 <- "SELECT c.city, p.productLine,
SUM(od.quantityOrdered) AS totalQuantity
FROM customers c
JOIN orders o ON c.customerNumber = o.customerNumber
JOIN orderdetails od ON o.orderNumber = od.orderNumber
JOIN products p ON od.productCode = p.productCode
WHERE c.country = 'Norway'
GROUP BY c.city, p.productLine"
query4## [1] "SELECT c.city, p.productLine,\nSUM(od.quantityOrdered) AS totalQuantity\nFROM customers c\nJOIN orders o ON c.customerNumber = o.customerNumber\nJOIN orderdetails od ON o.orderNumber = od.orderNumber\nJOIN products p ON od.productCode = p.productCode\nWHERE c.country = 'Norway'\nGROUP BY c.city, p.productLine"data4 <- dbGetQuery(con2, query4)
data4## city productLine totalQuantity
## 1 Stavern Classic Cars 267
## 2 Stavern Trucks and Buses 308
## 3 Stavern Vintage Cars 223
## 4 Stavern Motorcycles 212
## 5 Stavern Trains 72
## 6 Bergen Classic Cars 522
## 7 Bergen Motorcycles 272
## 8 Bergen Planes 29
## 9 Bergen Vintage Cars 150
## 10 Oslo Planes 296
## 11 Oslo Vintage Cars 122
## 12 Oslo Classic Cars 369ggplot(data4, aes(x = productLine, y = city, fill = totalQuantity)) +
geom_tile(color = "white") +
scale_fill_gradient(low = "lightblue", high = "darkblue") +
theme_minimal() +
labs(title = "Heatmap Penjualan Product Line di Kota-Kota Norway",
x = "Product Line",
y = "Kota",
fill = "Total Quantity") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))