Tugas Praktikum Visualisasi Data
Adinda Shabrina Putri Salsabila (G1401221081)
2024-02-05
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library(treemap)## Warning: package 'treemap' was built under R version 4.2.3INPUT DATA
datavisdat1 <- read.csv("C:/Users/hp/Documents/KULIAH/SEMESTER 4/VISDAT/2023 Maret JABAR - SUSENAS KOR INDIVIDU PART1.csv")
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## 328 NA I
## 329 NA
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## 336 NA
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## 341 A NA
## 342 NA
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## 344 NA
## 345 NA
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## 347 NA
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## 352 NA I
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## 354 NA
## 355 NA I
## 356 NA
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## 365 NA
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## 368 NA I
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## 404 NA
## 405 NA
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## 407 NA
## 408 NA
## 409 NA
## 410 NA I
## 411 NA
## 412 NA
## 413 NA
## 414 NA
## 415 NA
## 416 NA
## 417 NA
## 418 NA
## 419 NA
## 420 NA
## 421 NA
## 422 NA
## 423 NA
## 424 NA
## 425 NA
## 426 NA
## 427 NA
## 428 NA
## 429 NA
## 430 NA I
## 431 NA
## 432 NA
## 433 NA
## 434 NA
## 435 NA
## 436 NA
## 437 NA
## 438 NA
## 439 NA
## 440 NA
## 441 NA
## 442 NA I
## 443 NA
## 444 NA
## 445 NA
## 446 NA
## 447 NA
## 448 NA I
## 449 NA
## 450 NA
## 451 NA
## 452 NA
## 453 NA
## 454 NA
## 455 NA
## 456 NA
## 457 NA
## 458 NA
## 459 NA
## 460 NA
## 461 NA
## 462 NA
## 463 NA
## 464 NA
## 465 NA
## 466 NA
## 467 NA
## 468 NA
## 469 NA
## 470 NA
## 471 NA
## 472 NA I
## 473 NA
## 474 NA
## 475 NA
## 476 NA
## 477 NA
## 478 NA
## 479 NA I
## 480 NA
## 481 NA
## 482 NA
## 483 NA I
## 484 NA
## 485 NA
## 486 NA
## 487 NA
## 488 NA
## 489 NA
## 490 NA
## 491 NA
## 492 NA
## 493 NA
## 494 NA
## 495 NA
## 496 NA
## 497 NA
## 498 NA
## 499 NA
## 500 NA
## 501 NA
## 502 NA
## 503 NA
## 504 NA
## 505 NA
## 506 NA
## 507 NA I
## 508 NA
## 509 NA
## 510 NA
## 511 NA
## 512 NA
## 513 NA
## 514 NA
## 515 NA
## 516 A NA
## 517 A NA
## 518 NA I
## 519 NA
## 520 NA
## 521 NA
## 522 NA
## 523 NA
## 524 NA
## 525 NA
## 526 NA
## 527 NA
## 528 NA
## 529 NA G I
## 530 NA
## 531 NA
## 532 NA
## 533 NA
## 534 NA
## 535 NA
## 536 NA
## 537 NA
## 538 NA
## 539 NA
## 540 NA
## 541 NA
## 542 NA
## 543 NA
## 544 NA
## 545 NA
## 546 NA
## R1201 R1202_A R1202_B R1202_C R1202_D R1202_E R1202_F R1202_G R1203 R1204_A
## 1 5 NA 0
## 2 5 NA 0
## 3 5 NA 0
## 4 5 NA 0
## 5 5 NA 0
## 6 5 NA 0
## 7 5 NA 0
## 8 5 NA 0
## 9 5 NA 0
## 10 5 NA 0
## 11 5 NA 0
## 12 5 NA 0
## 13 5 NA 0
## 14 5 NA 0
## 15 5 NA 0
## 16 5 NA 0
## 17 5 NA 0
## 18 5 NA 0
## 19 5 NA 0
## 20 5 NA 0
## 21 5 NA 0
## 22 5 NA 0
## 23 1 B NA 5
## 24 5 NA 0
## 25 5 NA 0
## 26 5 NA 0
## 27 5 NA 0
## 28 5 NA 0
## 29 5 NA 0
## 30 5 NA 0
## 31 5 NA 0
## 32 5 NA 0
## 33 5 NA 0
## 34 5 NA 0
## 35 5 NA 0
## 36 5 NA 0
## 37 5 NA 0
## 38 5 NA 0
## 39 5 NA 0
## 40 5 NA 0
## 41 5 NA 0
## 42 5 NA 0
## 43 5 NA 0
## 44 5 NA 0
## 45 5 NA 0
## 46 5 NA 0
## 47 5 NA 0
## 48 5 NA 0
## 49 5 NA 0
## 50 5 NA 0
## 51 5 NA 0
## 52 5 NA 0
## 53 5 NA 0
## 54 5 NA 0
## 55 5 NA 0
## 56 5 NA 0
## 57 5 NA 0
## 58 5 NA 0
## 59 5 NA 0
## 60 5 NA 0
## 61 5 NA 0
## 62 5 NA 0
## 63 5 NA 0
## 64 5 NA 0
## 65 5 NA 0
## 66 5 NA 0
## 67 1 A NA 4
## 68 5 NA 0
## 69 5 NA 0
## 70 5 NA 0
## 71 5 NA 0
## 72 5 NA 0
## 73 5 NA 0
## 74 5 NA 0
## 75 5 NA 0
## 76 5 NA 0
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## 78 5 NA 0
## 79 5 NA 0
## 80 5 NA 0
## 81 5 NA 0
## 82 5 NA 0
## 83 5 NA 0
## 84 5 NA 0
## 85 5 NA 0
## 86 5 NA 0
## 87 5 NA 0
## 88 5 NA 0
## 89 5 NA 0
## 90 5 NA 0
## 91 5 NA 0
## 92 5 NA 0
## 93 5 NA 0
## 94 5 NA 0
## 95 5 NA 0
## 96 5 NA 0
## 97 5 NA 0
## 98 5 NA 0
## 99 5 NA 0
## 100 5 NA 0
## 101 5 NA 0
## 102 5 NA 0
## 103 5 NA 0
## 104 5 NA 0
## 105 5 NA 0
## 106 5 NA 0
## 107 5 NA 0
## 108 5 NA 0
## 109 5 NA 0
## 110 5 NA 0
## 111 5 NA 0
## 112 5 NA 0
## 113 5 NA 0
## 114 5 NA 0
## 115 5 NA 0
## 116 5 NA 0
## 117 5 NA 0
## 118 5 NA 0
## 119 5 NA 0
## 120 5 NA 0
## 121 5 NA 0
## 122 5 NA 0
## 123 1 B NA 4
## 124 5 NA 0
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## 129 5 NA 0
## 130 5 NA 0
## 131 5 NA 0
## 132 1 A NA 4
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## 134 5 NA 0
## 135 5 NA 0
## 136 5 NA 0
## 137 5 NA 0
## 138 5 NA 0
## 139 5 NA 0
## 140 5 NA 0
## 141 5 NA 0
## 142 5 NA 0
## 143 5 NA 0
## 144 5 NA 0
## 145 5 NA 0
## 146 5 NA 0
## 147 5 NA 0
## 148 5 NA 0
## 149 5 NA 0
## 150 5 NA 0
## 151 5 NA 0
## 152 5 NA 0
## 153 5 NA 0
## 154 5 NA 0
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## 157 5 NA 0
## 158 5 NA 0
## 159 5 NA 0
## 160 5 NA 0
## 161 5 NA 0
## 162 5 NA 0
## 163 5 NA 0
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## 170 5 NA 0
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## 173 5 NA 0
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## 181 1 B NA 5
## 182 5 NA 0
## 183 5 NA 0
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## 186 5 NA 0
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## 190 5 NA 0
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## 194 5 NA 0
## 195 5 NA 0
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## 197 5 NA 0
## 198 5 NA 0
## 199 5 NA 0
## 200 5 NA 0
## 201 5 NA 0
## 202 5 NA 0
## 203 5 NA 0
## 204 1 E NA 4
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## 206 1 E NA 2
## 207 5 NA 0
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## 215 5 NA 0
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## 217 5 NA 0
## 218 5 NA 0
## 219 5 NA 0
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## 221 5 NA 0
## 222 1 A NA 3
## 223 5 NA 0
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## 227 5 NA 0
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## 229 5 NA 0
## 230 5 NA 0
## 231 5 NA 0
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## 233 5 NA 0
## 234 5 NA 0
## 235 5 NA 0
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## 241 5 NA 0
## 242 5 NA 0
## 243 5 NA 0
## 244 5 NA 0
## 245 5 NA 0
## 246 5 NA 0
## 247 5 NA 0
## 248 5 NA 0
## 249 5 NA 0
## 250 5 NA 0
## 251 5 NA 0
## 252 5 NA 0
## 253 5 NA 0
## 254 5 NA 0
## 255 5 NA 0
## 256 5 NA 0
## 257 5 NA 0
## 258 5 NA 0
## 259 5 NA 0
## 260 5 NA 0
## 261 5 NA 0
## 262 5 NA 0
## 263 5 NA 0
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## 265 5 NA 0
## 266 5 NA 0
## 267 5 NA 0
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## 269 5 NA 0
## 270 5 NA 0
## 271 5 NA 0
## 272 5 NA 0
## 273 5 NA 0
## 274 5 NA 0
## 275 5 NA 0
## 276 5 NA 0
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## 280 5 NA 0
## 281 5 NA 0
## 282 5 NA 0
## 283 5 NA 0
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## 285 5 NA 0
## 286 5 NA 0
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## 290 5 NA 0
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## 293 5 NA 0
## 294 5 NA 0
## 295 5 NA 0
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## 298 5 NA 0
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## 302 5 NA 0
## 303 5 NA 0
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## 358 5 NA 0
## 359 5 NA 0
## 360 5 NA 0
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## 362 5 NA 0
## 363 5 NA 0
## 364 5 NA 0
## 365 5 NA 0
## 366 5 NA 0
## 367 5 NA 0
## 368 5 NA 0
## 369 5 NA 0
## 370 5 NA 0
## 371 5 NA 0
## 372 1 A NA 15 A
## 373 5 NA 0
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## 380 5 NA 0
## 381 5 NA 0
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## 385 5 NA 0
## 386 5 NA 0
## 387 5 NA 0
## 388 5 NA 0
## 389 5 NA 0
## 390 5 NA 0
## 391 5 NA 0
## 392 5 NA 0
## 393 5 NA 0
## 394 5 NA 0
## 395 1 A NA 7 A
## 396 5 NA 0
## 397 5 NA 0
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## 400 5 NA 0
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## 402 5 NA 0
## 403 5 NA 0
## 404 5 NA 0
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## 409 5 NA 0
## 410 5 NA 0
## 411 5 NA 0
## 412 5 NA 0
## 413 5 NA 0
## 414 5 NA 0
## 415 5 NA 0
## 416 5 NA 0
## 417 5 NA 0
## 418 1 B NA 3 A
## 419 1 B NA 3
## 420 5 NA 0
## 421 5 NA 0
## 422 5 NA 0
## 423 5 NA 0
## 424 5 NA 0
## 425 5 NA 0
## 426 5 NA 0
## 427 5 NA 0
## 428 5 NA 0
## 429 5 NA 0
## 430 5 NA 0
## 431 5 NA 0
## 432 5 NA 0
## 433 5 NA 0
## 434 1 B NA 3
## 435 5 NA 0
## 436 5 NA 0
## 437 5 NA 0
## 438 5 NA 0
## 439 5 NA 0
## 440 1 D NA 1
## 441 5 NA 0
## 442 5 NA 0
## 443 5 NA 0
## 444 5 NA 0
## 445 5 NA 0
## 446 5 NA 0
## 447 5 NA 0
## 448 5 NA 0
## 449 5 NA 0
## 450 5 NA 0
## 451 5 NA 0
## 452 5 NA 0
## 453 5 NA 0
## 454 5 NA 0
## 455 1 E NA 7 A
## 456 5 NA 0
## 457 5 NA 0
## 458 5 NA 0
## 459 5 NA 0
## 460 1 D NA 3
## 461 5 NA 0
## 462 5 NA 0
## 463 5 NA 0
## 464 5 NA 0
## 465 5 NA 0
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## 471 5 NA 0
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## 480 5 NA 0
## 481 5 NA 0
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## 483 5 NA 0
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## 485 5 NA 0
## 486 5 NA 0
## 487 5 NA 0
## 488 5 NA 0
## 489 5 NA 0
## 490 5 NA 0
## 491 5 NA 0
## 492 5 NA 0
## 493 5 NA 0
## 494 5 NA 0
## 495 5 NA 0
## 496 5 NA 0
## 497 5 NA 0
## 498 5 NA 0
## 499 5 NA 0
## 500 5 NA 0
## 501 5 NA 0
## 502 5 NA 0
## 503 5 NA 0
## 504 5 NA 0
## 505 5 NA 0
## 506 5 NA 0
## 507 5 NA 0
## 508 5 NA 0
## 509 5 NA 0
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## 513 5 NA 0
## 514 5 NA 0
## 515 5 NA 0
## 516 5 NA 0
## 517 5 NA 0
## 518 5 NA 0
## 519 5 NA 0
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## 521 5 NA 0
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## 523 5 NA 0
## 524 5 NA 0
## 525 5 NA 0
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## 529 5 NA 0
## 530 5 NA 0
## 531 5 NA 0
## 532 5 NA 0
## 533 5 NA 0
## 534 5 NA 0
## 535 5 NA 0
## 536 5 NA 0
## 537 5 NA 0
## 538 5 NA 0
## 539 5 NA 0
## 540 5 NA 0
## 541 5 NA 0
## 542 5 NA 0
## 543 5 NA 0
## 544 5 NA 0
## 545 5 NA 0
## 546 5 NA 0
## R1204_B R1204_C R1204_D R1204_E R1204_X R1205_A R1205_B R1205_C R1205_D
## 1
## 2
## 3
## 4
## 5
## 6
## 7
## 8
## 9
## 10
## 11
## 12
## 13
## 14
## 15
## 16
## 17
## 18
## 19
## 20
## 21
## 22
## 23 B
## 24
## 25
## 26
## 27
## 28
## 29
## 30
## 31
## 32
## 33
## 34
## 35
## 36
## 37
## 38
## 39
## 40
## 41
## 42
## 43
## 44
## 45
## 46
## 47
## 48
## 49
## 50
## 51
## 52
## 53
## 54
## 55
## 56
## 57
## 58
## 59
## 60
## 61
## 62
## 63
## 64
## 65
## 66
## 67 B
## 68
## 69
## 70
## 71
## 72
## 73
## 74
## 75
## 76
## 77
## 78
## 79
## 80
## 81
## 82
## 83
## 84
## 85
## 86
## 87
## 88
## 89
## 90
## 91
## 92
## 93
## 94
## 95
## 96
## 97
## 98
## 99
## 100
## 101
## 102
## 103
## 104
## 105
## 106
## 107
## 108
## 109
## 110
## 111
## 112
## 113
## 114
## 115
## 116
## 117
## 118
## 119
## 120
## 121
## 122
## 123 B
## 124
## 125
## 126
## 127
## 128
## 129
## 130
## 131
## 132 X
## 133
## 134
## 135
## 136
## 137
## 138
## 139
## 140
## 141
## 142
## 143
## 144
## 145
## 146
## 147
## 148
## 149
## 150
## 151
## 152
## 153
## 154
## 155
## 156
## 157
## 158
## 159
## 160
## 161
## 162
## 163
## 164
## 165
## 166
## 167
## 168
## 169
## 170
## 171
## 172
## 173
## 174
## 175
## 176
## 177
## 178
## 179
## 180
## 181 X B
## 182
## 183
## 184
## 185
## 186
## 187
## 188
## 189
## 190
## 191
## 192
## 193
## 194
## 195
## 196
## 197
## 198
## 199
## 200
## 201
## 202
## 203
## 204 X
## 205
## 206 B
## 207
## 208
## 209
## 210
## 211
## 212
## 213
## 214
## 215
## 216
## 217
## 218
## 219
## 220
## 221
## 222 X
## 223
## 224
## 225
## 226
## 227
## 228
## 229
## 230
## 231
## 232
## 233
## 234
## 235
## 236
## 237
## 238
## 239
## 240
## 241
## 242
## 243
## 244
## 245
## 246
## 247
## 248
## 249
## 250
## 251
## 252
## 253
## 254
## 255
## 256
## 257
## 258
## 259
## 260
## 261
## 262
## 263
## 264
## 265
## 266
## 267
## 268
## 269
## 270
## 271
## 272
## 273
## 274
## 275
## 276
## 277
## 278
## 279
## 280
## 281
## 282
## 283
## 284
## 285
## 286
## 287
## 288
## 289
## 290
## 291
## 292
## 293
## 294
## 295
## 296
## 297
## 298
## 299
## 300
## 301
## 302
## 303
## 304
## 305
## 306
## 307
## 308
## 309
## 310
## 311
## 312
## 313
## 314
## 315
## 316
## 317
## 318
## 319
## 320
## 321
## 322
## 323
## 324
## 325
## 326
## 327
## 328
## 329
## 330
## 331
## 332
## 333
## 334
## 335
## 336
## 337
## 338
## 339
## 340
## 341
## 342
## 343
## 344
## 345
## 346
## 347
## 348
## 349
## 350
## 351
## 352
## 353
## 354
## 355
## 356
## 357
## 358
## 359
## 360
## 361
## 362
## 363
## 364
## 365
## 366
## 367
## 368
## 369
## 370
## 371
## 372
## 373
## 374
## 375
## 376
## 377
## 378
## 379
## 380
## 381
## 382
## 383
## 384
## 385
## 386
## 387
## 388
## 389
## 390
## 391
## 392
## 393
## 394
## 395
## 396
## 397
## 398
## 399
## 400
## 401
## 402
## 403
## 404
## 405
## 406
## 407
## 408
## 409
## 410
## 411
## 412
## 413
## 414
## 415
## 416
## 417
## 418
## 419 X
## 420
## 421
## 422
## 423
## 424
## 425
## 426
## 427
## 428
## 429
## 430
## 431
## 432
## 433
## 434 B
## 435
## 436
## 437
## 438
## 439
## 440 X
## 441
## 442
## 443
## 444
## 445
## 446
## 447
## 448
## 449
## 450
## 451
## 452
## 453
## 454
## 455
## 456
## 457
## 458
## 459
## 460 X
## 461
## 462
## 463
## 464
## 465
## 466
## 467
## 468
## 469
## 470
## 471
## 472
## 473
## 474
## 475
## 476
## 477
## 478
## 479
## 480
## 481
## 482
## 483
## 484
## 485
## 486
## 487
## 488
## 489
## 490
## 491
## 492
## 493
## 494
## 495
## 496
## 497
## 498
## 499
## 500
## 501
## 502
## 503
## 504
## 505
## 506
## 507
## 508
## 509
## 510
## 511
## 512
## 513
## 514
## 515
## 516
## 517
## 518
## 519
## 520
## 521
## 522
## 523
## 524
## 525
## 526
## 527
## 528
## 529
## 530
## 531
## 532
## 533
## 534
## 535
## 536
## 537
## 538
## 539
## 540
## 541
## 542
## 543
## 544
## 545
## 546
## R1205_E R1205_F R1205_G R1205_H R1205_I R1206 R1207 R1208 R1209 FWT
## 1 NA 5 5 0 5 454.889101
## 2 NA 5 5 0 5 454.889101
## 3 NA 5 5 0 5 454.889101
## 4 NA 5 5 0 5 454.889101
## 5 NA 5 5 0 5 172.376821
## 6 NA 5 1 35 1 172.376821
## 7 NA 5 1 49 1 241.578661
## 8 NA 5 5 0 5 241.578661
## 9 NA 5 5 0 5 241.578661
## 10 NA 5 1 112 1 93.673563
## 11 NA 5 1 14 1 93.673563
## 12 NA 5 5 0 5 93.673563
## 13 NA 5 5 0 5 93.673563
## 14 NA 5 5 0 5 93.673563
## 15 NA 0 0 0 0 93.673563
## 16 NA 5 5 0 5 93.673563
## 17 NA 5 2 48 2 122.217556
## 18 NA 5 5 0 5 122.217556
## 19 NA 5 5 0 5 122.217556
## 20 NA 5 5 0 5 7.638085
## 21 NA 5 5 0 5 7.638085
## 22 NA 5 5 0 5 47.200020
## 23 NA 5 5 0 5 47.200020
## 24 NA 5 5 0 5 740.430683
## 25 NA 5 5 0 5 740.430683
## 26 NA 5 1 42 1 740.430683
## 27 NA 5 5 0 5 740.430683
## 28 NA 5 5 0 5 740.430683
## 29 NA 5 5 0 5 740.430683
## 30 NA 5 1 84 1 242.224484
## 31 NA 5 5 0 5 242.224484
## 32 NA 5 1 60 1 1342.143299
## 33 NA 5 5 0 5 1342.143299
## 34 NA 5 5 0 5 1342.143299
## 35 NA 0 0 0 0 1342.143299
## 36 NA 5 1 35 1 2550.590230
## 37 NA 5 5 0 5 2550.590230
## 38 NA 5 1 49 1 2550.590230
## 39 NA 5 5 0 5 1106.673762
## 40 NA 5 5 0 5 1106.673762
## 41 NA 5 5 0 5 1106.673762
## 42 NA 0 0 0 0 1106.673762
## 43 NA 0 0 0 0 1106.673762
## 44 NA 5 1 48 1 1635.263517
## 45 NA 5 5 0 5 1635.263517
## 46 NA 5 5 0 5 1635.263517
## 47 NA 5 5 0 5 1635.263517
## 48 NA 0 0 0 0 1635.263517
## 49 NA 5 1 126 1 401.591597
## 50 NA 5 5 0 5 401.591597
## 51 NA 5 5 0 5 401.591597
## 52 NA 5 5 0 5 135.235495
## 53 NA 5 5 0 5 135.235495
## 54 NA 5 1 84 1 135.235495
## 55 NA 5 5 0 5 135.235495
## 56 NA 5 5 0 5 41.151278
## 57 NA 5 5 0 5 41.151278
## 58 NA 5 1 84 1 676.335579
## 59 NA 5 5 0 5 676.335579
## 60 NA 5 5 0 5 676.335579
## 61 NA 5 5 0 5 676.335579
## 62 NA 5 5 0 5 676.335579
## 63 NA 0 0 0 0 676.335579
## 64 NA 5 1 168 1 694.279008
## 65 NA 5 5 0 5 694.279008
## 66 NA 0 0 0 0 694.279008
## 67 NA 0 0 0 0 694.279008
## 68 NA 5 1 336 1 46.774935
## 69 NA 5 5 0 5 46.774935
## 70 NA 5 5 0 5 46.774935
## 71 NA 5 5 0 5 46.774935
## 72 NA 0 0 0 0 46.774935
## 73 NA 5 5 0 5 376.830372
## 74 NA 5 5 0 5 376.830372
## 75 NA 5 2 7 2 478.596497
## 76 NA 5 5 0 5 478.596497
## 77 NA 5 1 84 1 294.936751
## 78 NA 5 5 0 5 294.936751
## 79 NA 5 5 0 5 294.936751
## 80 NA 5 1 84 1 489.241534
## 81 NA 5 5 0 5 489.241534
## 82 NA 5 5 0 5 489.241534
## 83 NA 5 5 0 5 489.241534
## 84 NA 5 1 84 1 1416.521124
## 85 NA 5 5 0 5 1416.521124
## 86 NA 5 5 0 5 1416.521124
## 87 NA 5 5 0 5 1416.521124
## 88 NA 0 0 0 0 1416.521124
## 89 NA 0 0 0 0 1416.521124
## 90 NA 5 5 0 5 199.855262
## 91 NA 5 5 0 5 199.855262
## 92 NA 5 5 0 5 654.560240
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## 459 NA 5 5 0 5 175.188614
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## 523 NA 0 0 0 0 320.486257
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## 525 NA 5 5 0 5 935.350236
## 526 NA 5 1 84 1 935.350236
## 527 NA 5 1 84 1 935.350236
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## 530 NA 5 5 0 5 919.081641
## 531 NA 5 5 0 5 199.976731
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## 534 NA 5 5 0 5 199.976731
## 535 NA 0 0 0 0 199.976731
## 536 NA 5 1 126 1 156.540322
## 537 NA 5 5 0 5 156.540322
## 538 NA 5 5 0 5 156.540322
## 539 NA 5 1 84 1 797.946347
## 540 NA 5 5 0 5 797.946347
## 541 NA 5 1 42 1 797.946347
## 542 NA 5 1 112 1 1635.871447
## 543 NA 5 5 0 5 1635.871447
## 544 NA 5 2 48 2 1635.871447
## 545 NA 5 2 36 2 1635.871447
## 546 NA 5 5 0 5 1635.871447
## [ reached 'max' / getOption("max.print") -- omitted 84142 rows ]data_peubah <- data.frame(
kode_kabupaten = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,71,72,73,74,75,76,77,78,79),
nama_kabupaten = c("KAB. BOGOR", "KAB. SUKABUMI", "KAB. CIANJUR", "KAB. BANDUNG", "KAB. GARUT", "KAB. TASIKMALAYA", "KAB. CIAMIS", "KAB. KUNINGAN", "KAB. CIREBON", "KAB. MAJALENGKA", "KAB. SUMEDANG", "KAB. INDRAMAYU", "KAB. SUBANG", "KAB. PURWAKARTA", "KAB. KARAWANG", "KAB. BEKASI", "KAB. BANDUNG BARAT", "KAB. PANGANDARAN", "KOTA BOGOR", "KOTA SUKABUMI", "KOTA BANDUNG", "KOTA CIREBON", "KOTA BEKASI", "KOTA DEPOK", "KOTA CIMAHI", "KOTA TASIKMALAYA", "KOTA BANJAR"),
kode_kedudukan = c(1,2,3,4,5,6,7,8,9),
nama_kedudukan = c("Suami", "Istri", "Anak Kandung", "Anak Angkat", "Menantu", "Cucu", "Mertua", "Pembantu", "Lainnya")
)
Databaru1 <- left_join(datavisdat1, data_peubah, by = c("R102"= "kode_kabupaten", "R403"= "kode_kedudukan"))
str(Databaru1)## 'data.frame': 84688 obs. of 185 variables:
## $ X : int 0 1 2 3 4 5 6 7 8 9 ...
## $ URUT : int 500001 500001 500001 500001 500002 500002 500003 500003 500003 500004 ...
## $ PSU : int 12448 12448 12448 12448 31373 31373 12092 12092 12092 31135 ...
## $ SSU : int 123442 123442 123442 123442 311039 311039 119908 119908 119908 308689 ...
## $ WI1 : int 12435 12435 12435 12435 31360 31360 12079 12079 12079 31122 ...
## $ WI2 : int 123427 123427 123427 123427 311024 311024 119893 119893 119893 308674 ...
## $ R101 : int 32 32 32 32 32 32 32 32 32 32 ...
## $ R102 : num 7 7 7 7 72 72 6 6 6 72 ...
## $ R105 : int 2 2 2 2 1 1 2 2 2 1 ...
## $ R401 : int 1 2 3 4 1 2 1 2 3 1 ...
## $ R403 : num 1 3 6 6 1 3 1 2 3 1 ...
## $ R404 : int 4 2 1 1 3 1 2 2 1 2 ...
## $ R405 : int 2 2 2 1 2 1 1 2 2 1 ...
## $ R407 : int 68 46 16 6 62 38 54 41 10 40 ...
## $ R408 : int 0 5 0 0 0 0 1 1 0 1 ...
## $ R409 : int 20 22 0 0 16 0 27 18 0 16 ...
## $ R406A : int 5 2 23 17 6 28 10 12 21 26 ...
## $ R406B : int 4 10 1 8 12 7 11 11 4 3 ...
## $ R406C : int 1954 1976 2007 2016 1960 1984 1968 1981 2012 1982 ...
## $ R410 : int 2 2 2 2 1 1 2 2 2 2 ...
## $ R501 : int 1 1 0 0 2 0 1 1 0 1 ...
## $ R502 : int 1 2 3 4 1 1 1 1 1 1 ...
## $ R503 : int 0 1 2 2 0 1 0 0 2 0 ...
## $ R504 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ R506 : int 2 2 2 1 2 1 1 2 2 1 ...
## $ R507 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ R508 : int 5 2 2 2 2 1 5 5 1 1 ...
## $ R509 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ R601 : int 32 32 32 32 32 32 32 32 32 32 ...
## $ R602 : int 7 7 7 7 72 72 6 6 6 72 ...
## $ R603 : int 32 32 32 32 32 32 32 32 32 32 ...
## $ R604 : int 7 7 7 7 72 72 6 6 6 72 ...
## $ R605 : int 0 0 0 3 0 0 0 0 4 0 ...
## $ R606 : int 0 0 0 1 0 0 0 0 0 0 ...
## $ R607 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ R608 : int 1 1 1 1 5 5 1 1 1 1 ...
## $ R609 : int 5 5 5 5 5 5 5 5 5 5 ...
## $ R610 : int 3 3 3 2 3 3 3 3 2 3 ...
## $ R611 : int 0 0 0 1 0 0 0 0 1 0 ...
## $ R612 : int 3 19 15 3 3 3 13 8 3 8 ...
## $ R613 : int 8 8 1 1 8 8 8 8 5 8 ...
## $ R614 : int 3 19 8 25 3 3 13 8 25 8 ...
## $ R615 : int 0 0 5 5 0 0 0 0 5 0 ...
## $ R616 : int 0 0 5 5 0 0 0 0 5 0 ...
## $ R617 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ R618 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ R619 : int 0 0 3 1 0 0 0 0 2 0 ...
## $ R620 : int 0 0 0 0 0 0 0 0 3 0 ...
## $ R621 : int 0 0 0 0 0 0 0 0 4 0 ...
## $ R701 : int 1 1 5 5 5 1 1 5 5 1 ...
## $ R702 : int 1 5 5 5 5 5 1 5 5 1 ...
## $ R703_A : chr "" "" "" "" ...
## $ R703_B : chr "" "" "" "" ...
## $ R703_C : chr "C" "C" "C" "" ...
## $ R703_D : chr "D" "D" "D" "" ...
## $ R703_X : chr "" "" "" "" ...
## $ R704 : int 3 3 3 0 3 1 1 3 2 1 ...
## $ R705 : int 5 5 5 0 5 0 0 5 5 0 ...
## $ R706 : int 0 0 0 0 0 11 12 0 0 13 ...
## $ R707 : int 0 0 0 0 0 5 1 0 0 4 ...
## $ R708 : int 0 0 0 0 0 48 50 0 0 48 ...
## $ R709 : int 0 0 0 0 0 48 50 0 0 97 ...
## $ R801 : int 5 1 1 5 1 1 1 1 1 1 ...
## $ R802 : int 5 1 1 5 1 1 1 1 1 1 ...
## $ R807_A : chr "" "" "" "" ...
## $ R807_B : chr "" "" "B" "" ...
## $ R807_C : chr "" "" "" "" ...
## $ R807_X : chr "X" "X" "" "X" ...
## $ R808 : int 5 1 1 5 5 5 1 1 1 1 ...
## $ R809_A : chr "" "" "" "" ...
## $ R809_B : chr "" "" "B" "" ...
## $ R809_C : chr "" "" "" "" ...
## $ R809_D : chr "" "D" "D" "" ...
## $ R809_E : chr "" "" "" "" ...
## $ R810_A : chr "" "A" "A" "" ...
## $ R810_B : chr "" "" "" "" ...
## $ R810_C : chr "" "" "" "" ...
## $ R810_D : chr "" "" "D" "" ...
## $ R810_E : chr "" "E" "" "" ...
## $ R810_F : logi NA FALSE FALSE NA NA NA ...
## $ R811_A : chr "" "A" "" "" ...
## $ R811_B : chr "" "B" "" "" ...
## $ R811_C : chr "" "" "" "" ...
## $ R811_D : chr "" "D" "D" "" ...
## $ R811_E : chr "" "" "" "" ...
## $ R811_F : logi NA NA NA NA NA NA ...
## $ R811_G : chr "" "" "" "" ...
## $ R811_H : chr "" "" "H" "" ...
## $ R811_I : chr "" "" "" "" ...
## $ R811_J : chr "" "J" "J" "" ...
## $ R811_K : chr "" "" "" "" ...
## $ R811_L : chr "" "" "" "" ...
## $ R812 : int 5 5 1 5 5 5 5 5 5 5 ...
## $ R901 : int 5 5 5 5 5 5 5 5 5 5 ...
## $ R902 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ R903 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ R904 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ R905 : int 5 5 5 5 5 5 5 5 5 5 ...
## $ R906 : int 0 0 0 0 0 0 0 0 0 0 ...
## [list output truncated]VISUALISASI BESARAN
Lollipop Chart
Databaru1 %>%
count(nama_kabupaten) %>%
arrange(desc(n)) %>%
ggplot() +
geom_segment(aes(x = fct_reorder(as.factor(nama_kabupaten), n), xend = fct_reorder(as.factor(nama_kabupaten), n), y = 0, yend = n), color = "pink") +
geom_point(aes(x = fct_reorder(as.factor(nama_kabupaten), n), y = n), color = "red", size = 2) +
scale_y_continuous(expand = c(0, 0)) +
coord_flip() +
ggtitle("Jumlah Responden SUSENAS per-Kabupaten/Kota di Jawa Barat") +
xlab("") +
ylab("Jumlah Individu") +
theme_light() +
theme(plot.title = element_text(hjust = 0.5))
Interpretasi
Berdasarkan output yang ditampilkan dari lollipop chart di atas, kita bisa melihat jumlah responden dari SUSENAS (Survei Sosial dan Ekonomi Nasional) di Provinsi Jawa Barat dari masing-masing kabupaten/kota. Terdapat 27 kabupaten/kota dengan jumlah sampel terbanyak yang diketahui diduduki oleh Kota Bandung dengan lebih dari 4500 responden, dilanjutkan oleh Kabupaten Cianjur, Kabupaten Bogor, hingga Kabupaten Subang dengan sampel paling rendah yaitu kurang dari 2000 responden. Sementara diketahui juga banyak sekali NA atau data tidak diketahui sebanyak lebih dari 70.000 responden yang tidak mengisi pertanyaan mengenai asal daerah mereka.
Bar Chart
Databaru1 %>%
count(nama_kedudukan) %>%
ggplot()+
geom_col(aes(x=fct_reorder(as.factor(nama_kedudukan),n),y=n), fill="purple",
width=0.4) +
geom_text(aes(x = fct_reorder(as.factor(nama_kedudukan), n), y = n, label = n),
position = position_stack(vjust = 0.5), color = "black", size = 3) +
scale_y_continuous(expand = c(0,0))+
coord_flip() +
ggtitle("Kedudukan Responden dalam Rumah Tangga") +
xlab("") +
ylab("Jumlah") +
theme_classic() +
theme(plot.title = element_text(hjust = .5, size = 10))
Interpretasi
Berdasarkan Bar chart di atas dapat dilihat bahwa nilai NA sangat banyak yaitu mencapai lebih dari 75 ribu responden dalam SUSENAS tidak mengisi form mengenai kedudukan mereka dalam rumah tangga sehingga terjadi kekosongan data. Adapun informasi kedudukan dalam rumah tangga yang dapat dilihat selanjutnya adalah kedudukan sebagai anak kandung dengan jumlah terbanyak kedua yaitu sebesar 4048, diikuti dengan suami, istri, hingga anak angkat dengan posisi paling rendah yaitu sebanyak 0 responden.
VISUALISASI SEBARAN
Histogram
datavisdat1 %>%
select(R407) %>%
mutate(R407 = as.numeric(R407)) %>%
ggplot()+
geom_histogram(aes(x=R407),binwidth=5,fill="orange")+
labs(title="Usia Masyarakat Jawa Barat Tahun 2023",x="Usia", y="Jumlah")+
theme_classic()
Interpretasi
Berdasarkan output histogram di atas, dapat terlihat bahwa grafik cenderung menjulur ke kanan dengan memiliki 2 titik puncak(bimodus). Modus pertama berada pada rentang usia 5-15 tahun dan modus kedua ada di sekitar umur 35-45 tahun. Dapat disimpulkan bahwa masyarakat Jawabarat sebagian besar ditempati oleh kalangan anak-anak dan usia produktif.
Box Plot
datavisdat1 %>%
select(R407,R105) %>%
mutate(R407 = as.numeric(R407),
R105 = ifelse(R105==1,"Pedesaan","Perkotaan")) %>%
ggplot()+
geom_boxplot(aes(x=R105, color=R105,y=R407))+
labs(title="Sebaran Usia dengan Tempat Tinggal Saat Ini ",x="Tempat tinggal", y="Usia")+
theme_classic()
Interpretasi
Berdasarkan output boxplot di atas, sebaran usia dengan tempat tinggal tidak jauh berbeda. Namun jangkauan yang tinggal di perkotaan sedikit lebih besar dibandingkan yang tinggal di pedesaan. Begitu juga dengan rataan usianya, dimana masyarakat yang tinggal di perkotaan sedikit lebih besar dibandingkan yang tinggal di pedesaan.
VISUALISASI KOMPOSISI
Pie Chart
Pie_chart <- data.frame(
jenis_kelamin = c("Laki-laki", "Perempuan"),
count = table(cut(datavisdat1$R405, breaks=c(-Inf,1,2), labels=c("Laki-laki", "Perempuan")))
)
Pie_chart## jenis_kelamin count.Var1 count.Freq
## 1 Laki-laki Laki-laki 42722
## 2 Perempuan Perempuan 41966ggplot(Pie_chart, aes(x = "", y = count.Freq , fill = jenis_kelamin )) +
geom_bar(stat = "identity", width = 1) +
coord_polar("y", start = 0) +
scale_fill_brewer("Blues")+
theme_void() +
theme(legend.position = "right") +
labs(title = "Komposisi Jenis Kelamin", fill = "Laki2/Perempuan") +
geom_text(aes(label = count.Freq), position = position_stack(vjust = 0.5))
Interpretasi
Berdasarkan output pie chart di atas, dapat dilihat bahwa komposisi antara laki-laki dengan perempuan pada data SUSENAS Jawa Barat 2023 tidak berbeda jauh namun lebih banyak laki-laki, dimana laki-laki sebanyak 42.722 individu dan perempuan sebanyak 41.966 individu.
Tree Map
treemap(Databaru1,
index=c("nama_kabupaten", "R610"),
vSize="R102",
draw=TRUE,
title="Treemap: Keadaan Pendidikan Saat Ini di Jawa Barat",
fontsize.title=15,
fontsize.labels=10,
fontcolor.labels="black")
###### Interpretasi Berdasarkan output tree map di atas, diketahui bahwa
komposisi keadaan pendidikan di tiap kabupaten/kota cenderung
berbeda-beda. Angka 1=masyarakat belum bersekolah, 2=masih bersekolah,
dan 3=sudah tidak bersekolah. Misalnya Kota Bandung yang memiliki
komposisi terbesar mayoritas memiliki masyarakat yang masih bersekolah
kurang lebih sebanyak 50%.