library(tmap)
library(readr)
library(sf)
## Linking to GEOS 3.13.0, GDAL 3.10.1, PROJ 9.5.1; sf_use_s2() is TRUE
library(sp)
library(ggplot2)
library(ggstats)
library(gstat)
library(automap)
library(rnaturalearth)
library(rnaturalearthdata)
##
## Attaching package: 'rnaturalearthdata'
## The following object is masked from 'package:rnaturalearth':
##
## countries110
library(viridis)
## Loading required package: viridisLite
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
# Membaca data
data <- read.csv("C:/Users/abela/Downloads/pH_Banten.csv")
# Baca shapefile Provinsi Banten
shp<-st_read("C:/Users/abela/Downloads/RBI_50K_2023_Banten.x26272/RBI_50K_2023_Banten.shp")
## Reading layer `RBI_50K_2023_Banten' from data source
## `C:\Users\abela\Downloads\RBI_50K_2023_Banten.x26272\RBI_50K_2023_Banten.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 8 features and 25 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: 105.0999 ymin: -7.016281 xmax: 106.7799 ymax: -5.807588
## Geodetic CRS: WGS 84
# Melihat struktur data
str(data)
## 'data.frame': 1089 obs. of 3 variables:
## $ longitude: num 105 105 105 105 105 ...
## $ latitude : num -7.46 -7.46 -7.46 -7.46 -7.46 -7.46 -7.46 -7.46 -7.46 -7.46 ...
## $ ph : num 5.98 5.18 6.25 6.36 4.63 5.02 5.88 5.61 5.79 5.29 ...
# Melihat beberapa baris awal data
head(data)
## longitude latitude ph
## 1 104.8800 -7.46 5.98
## 2 104.9456 -7.46 5.18
## 3 105.0113 -7.46 6.25
## 4 105.0769 -7.46 6.36
## 5 105.1425 -7.46 4.63
## 6 105.2081 -7.46 5.02
# Membuat statistik deskriptif
summary(data)
## longitude latitude ph
## Min. :104.9 Min. :-7.460 Min. :4.000
## 1st Qu.:105.4 1st Qu.:-6.935 1st Qu.:5.390
## Median :105.9 Median :-6.410 Median :5.800
## Mean :105.9 Mean :-6.410 Mean :5.785
## 3rd Qu.:106.5 3rd Qu.:-5.885 3rd Qu.:6.150
## Max. :107.0 Max. :-5.360 Max. :7.710
# Menghitung statistik tambahan
mean(data$ph)
## [1] 5.78461
sd(data$ph)
## [1] 0.5889471
range(data$ph)
## [1] 4.00 7.71
# 1. Baca data CSV
print(data)
## longitude latitude ph
## 1 104.8800 -7.460000 5.98
## 2 104.9456 -7.460000 5.18
## 3 105.0113 -7.460000 6.25
## 4 105.0769 -7.460000 6.36
## 5 105.1425 -7.460000 4.63
## 6 105.2081 -7.460000 5.02
## 7 105.2738 -7.460000 5.88
## 8 105.3394 -7.460000 5.61
## 9 105.4050 -7.460000 5.79
## 10 105.4706 -7.460000 5.29
## 11 105.5362 -7.460000 6.33
## 12 105.6019 -7.460000 6.27
## 13 105.6675 -7.460000 5.84
## 14 105.7331 -7.460000 6.48
## 15 105.7987 -7.460000 6.08
## 16 105.8644 -7.460000 5.28
## 17 105.9300 -7.460000 6.02
## 18 105.9956 -7.460000 5.22
## 19 106.0613 -7.460000 6.33
## 20 106.1269 -7.460000 5.77
## 21 106.1925 -7.460000 5.69
## 22 106.2581 -7.460000 5.39
## 23 106.3238 -7.460000 6.53
## 24 106.3894 -7.460000 5.71
## 25 106.4550 -7.460000 5.54
## 26 106.5206 -7.460000 5.59
## 27 106.5863 -7.460000 6.12
## 28 106.6519 -7.460000 6.02
## 29 106.7175 -7.460000 6.05
## 30 106.7831 -7.460000 6.06
## 31 106.8487 -7.460000 7.08
## 32 106.9144 -7.460000 5.56
## 33 106.9800 -7.460000 5.49
## 34 104.8800 -7.394375 5.31
## 35 104.9456 -7.394375 6.17
## 36 105.0113 -7.394375 6.48
## 37 105.0769 -7.394375 5.73
## 38 105.1425 -7.394375 5.30
## 39 105.2081 -7.394375 5.31
## 40 105.2738 -7.394375 6.19
## 41 105.3394 -7.394375 6.25
## 42 105.4050 -7.394375 6.13
## 43 105.4706 -7.394375 5.40
## 44 105.5362 -7.394375 5.94
## 45 105.6019 -7.394375 5.87
## 46 105.6675 -7.394375 5.93
## 47 105.7331 -7.394375 6.32
## 48 105.7987 -7.394375 5.93
## 49 105.8644 -7.394375 6.21
## 50 105.9300 -7.394375 5.84
## 51 105.9956 -7.394375 5.97
## 52 106.0613 -7.394375 6.18
## 53 106.1269 -7.394375 4.93
## 54 106.1925 -7.394375 5.61
## 55 106.2581 -7.394375 5.52
## 56 106.3238 -7.394375 5.42
## 57 106.3894 -7.394375 5.63
## 58 106.4550 -7.394375 6.70
## 59 106.5206 -7.394375 5.28
## 60 106.5863 -7.394375 6.38
## 61 106.6519 -7.394375 4.79
## 62 106.7175 -7.394375 5.60
## 63 106.7831 -7.394375 5.90
## 64 106.8487 -7.394375 6.15
## 65 106.9144 -7.394375 6.23
## 66 106.9800 -7.394375 6.28
## 67 104.8800 -7.328750 5.59
## 68 104.9456 -7.328750 5.52
## 69 105.0113 -7.328750 6.31
## 70 105.0769 -7.328750 5.69
## 71 105.1425 -7.328750 5.03
## 72 105.2081 -7.328750 5.12
## 73 105.2738 -7.328750 5.25
## 74 105.3394 -7.328750 6.10
## 75 105.4050 -7.328750 5.89
## 76 105.4706 -7.328750 6.21
## 77 105.5362 -7.328750 5.54
## 78 105.6019 -7.328750 5.90
## 79 105.6675 -7.328750 6.18
## 80 105.7331 -7.328750 5.61
## 81 105.7987 -7.328750 6.07
## 82 105.8644 -7.328750 5.40
## 83 105.9300 -7.328750 5.58
## 84 105.9956 -7.328750 5.57
## 85 106.0613 -7.328750 5.08
## 86 106.1269 -7.328750 6.09
## 87 106.1925 -7.328750 5.52
## 88 106.2581 -7.328750 5.81
## 89 106.3238 -7.328750 6.09
## 90 106.3894 -7.328750 6.07
## 91 106.4550 -7.328750 6.20
## 92 106.5206 -7.328750 5.74
## 93 106.5863 -7.328750 5.55
## 94 106.6519 -7.328750 5.75
## 95 106.7175 -7.328750 4.79
## 96 106.7831 -7.328750 4.93
## 97 106.8487 -7.328750 5.01
## 98 106.9144 -7.328750 5.20
## 99 106.9800 -7.328750 6.04
## 100 104.8800 -7.263125 5.26
## 101 104.9456 -7.263125 5.57
## 102 105.0113 -7.263125 6.58
## 103 105.0769 -7.263125 5.59
## 104 105.1425 -7.263125 6.24
## 105 105.2081 -7.263125 5.24
## 106 105.2738 -7.263125 5.68
## 107 105.3394 -7.263125 5.23
## 108 105.4050 -7.263125 5.60
## 109 105.4706 -7.263125 6.30
## 110 105.5362 -7.263125 4.76
## 111 105.6019 -7.263125 6.06
## 112 105.6675 -7.263125 5.94
## 113 105.7331 -7.263125 5.44
## 114 105.7987 -7.263125 4.93
## 115 105.8644 -7.263125 5.84
## 116 105.9300 -7.263125 5.48
## 117 105.9956 -7.263125 5.94
## 118 106.0613 -7.263125 5.81
## 119 106.1269 -7.263125 6.76
## 120 106.1925 -7.263125 5.66
## 121 106.2581 -7.263125 5.19
## 122 106.3238 -7.263125 5.91
## 123 106.3894 -7.263125 5.93
## 124 106.4550 -7.263125 6.62
## 125 106.5206 -7.263125 6.30
## 126 106.5863 -7.263125 6.01
## 127 106.6519 -7.263125 6.68
## 128 106.7175 -7.263125 5.09
## 129 106.7831 -7.263125 5.42
## 130 106.8487 -7.263125 5.24
## 131 106.9144 -7.263125 5.57
## 132 106.9800 -7.263125 4.97
## 133 104.8800 -7.197500 6.18
## 134 104.9456 -7.197500 5.67
## 135 105.0113 -7.197500 4.92
## 136 105.0769 -7.197500 5.19
## 137 105.1425 -7.197500 5.99
## 138 105.2081 -7.197500 6.30
## 139 105.2738 -7.197500 7.00
## 140 105.3394 -7.197500 7.55
## 141 105.4050 -7.197500 6.05
## 142 105.4706 -7.197500 5.21
## 143 105.5362 -7.197500 4.52
## 144 105.6019 -7.197500 5.96
## 145 105.6675 -7.197500 5.31
## 146 105.7331 -7.197500 5.55
## 147 105.7987 -7.197500 5.43
## 148 105.8644 -7.197500 5.72
## 149 105.9300 -7.197500 6.44
## 150 105.9956 -7.197500 5.89
## 151 106.0613 -7.197500 5.70
## 152 106.1269 -7.197500 5.18
## 153 106.1925 -7.197500 4.80
## 154 106.2581 -7.197500 5.51
## 155 106.3238 -7.197500 5.77
## 156 106.3894 -7.197500 6.86
## 157 106.4550 -7.197500 5.88
## 158 106.5206 -7.197500 6.39
## 159 106.5863 -7.197500 5.50
## 160 106.6519 -7.197500 5.09
## 161 106.7175 -7.197500 5.22
## 162 106.7831 -7.197500 5.36
## 163 106.8487 -7.197500 7.08
## 164 106.9144 -7.197500 5.31
## 165 106.9800 -7.197500 6.30
## 166 104.8800 -7.131875 5.26
## 167 104.9456 -7.131875 6.36
## 168 105.0113 -7.131875 6.03
## 169 105.0769 -7.131875 5.71
## 170 105.1425 -7.131875 5.78
## 171 105.2081 -7.131875 5.41
## 172 105.2738 -7.131875 6.07
## 173 105.3394 -7.131875 5.53
## 174 105.4050 -7.131875 5.06
## 175 105.4706 -7.131875 5.03
## 176 105.5362 -7.131875 5.90
## 177 105.6019 -7.131875 6.75
## 178 105.6675 -7.131875 5.90
## 179 105.7331 -7.131875 5.73
## 180 105.7987 -7.131875 5.97
## 181 105.8644 -7.131875 6.58
## 182 105.9300 -7.131875 5.93
## 183 105.9956 -7.131875 5.55
## 184 106.0613 -7.131875 6.46
## 185 106.1269 -7.131875 6.06
## 186 106.1925 -7.131875 6.72
## 187 106.2581 -7.131875 5.91
## 188 106.3238 -7.131875 5.07
## 189 106.3894 -7.131875 4.98
## 190 106.4550 -7.131875 6.79
## 191 106.5206 -7.131875 6.83
## 192 106.5863 -7.131875 5.69
## 193 106.6519 -7.131875 5.57
## 194 106.7175 -7.131875 6.68
## 195 106.7831 -7.131875 5.14
## 196 106.8487 -7.131875 5.26
## 197 106.9144 -7.131875 6.19
## 198 106.9800 -7.131875 5.56
## 199 104.8800 -7.066250 5.80
## 200 104.9456 -7.066250 5.70
## 201 105.0113 -7.066250 6.00
## 202 105.0769 -7.066250 6.64
## 203 105.1425 -7.066250 5.85
## 204 105.2081 -7.066250 6.19
## 205 105.2738 -7.066250 4.57
## 206 105.3394 -7.066250 5.77
## 207 105.4050 -7.066250 5.29
## 208 105.4706 -7.066250 5.07
## 209 105.5362 -7.066250 5.27
## 210 105.6019 -7.066250 5.60
## 211 105.6675 -7.066250 6.35
## 212 105.7331 -7.066250 5.00
## 213 105.7987 -7.066250 5.82
## 214 105.8644 -7.066250 5.51
## 215 105.9300 -7.066250 5.60
## 216 105.9956 -7.066250 6.40
## 217 106.0613 -7.066250 6.12
## 218 106.1269 -7.066250 6.60
## 219 106.1925 -7.066250 5.71
## 220 106.2581 -7.066250 5.38
## 221 106.3238 -7.066250 5.67
## 222 106.3894 -7.066250 5.95
## 223 106.4550 -7.066250 5.91
## 224 106.5206 -7.066250 5.15
## 225 106.5863 -7.066250 5.85
## 226 106.6519 -7.066250 5.94
## 227 106.7175 -7.066250 7.31
## 228 106.7831 -7.066250 6.93
## 229 106.8487 -7.066250 5.29
## 230 106.9144 -7.066250 5.63
## 231 106.9800 -7.066250 4.92
## 232 104.8800 -7.000625 5.45
## 233 104.9456 -7.000625 5.99
## 234 105.0113 -7.000625 6.52
## 235 105.0769 -7.000625 5.36
## 236 105.1425 -7.000625 5.41
## 237 105.2081 -7.000625 4.51
## 238 105.2738 -7.000625 5.70
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## 240 105.4050 -7.000625 5.48
## 241 105.4706 -7.000625 5.27
## 242 105.5362 -7.000625 5.74
## 243 105.6019 -7.000625 4.75
## 244 105.6675 -7.000625 4.92
## 245 105.7331 -7.000625 7.08
## 246 105.7987 -7.000625 5.03
## 247 105.8644 -7.000625 5.14
## 248 105.9300 -7.000625 6.90
## 249 105.9956 -7.000625 7.54
## 250 106.0613 -7.000625 5.10
## 251 106.1269 -7.000625 5.58
## 252 106.1925 -7.000625 6.00
## 253 106.2581 -7.000625 6.84
## 254 106.3238 -7.000625 5.21
## 255 106.3894 -7.000625 5.65
## 256 106.4550 -7.000625 6.27
## 257 106.5206 -7.000625 6.06
## 258 106.5863 -7.000625 5.57
## 259 106.6519 -7.000625 5.72
## 260 106.7175 -7.000625 4.98
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## 268 105.0769 -6.935000 6.01
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## 272 105.3394 -6.935000 5.99
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## 275 105.5362 -6.935000 6.74
## 276 105.6019 -6.935000 6.03
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## 278 105.7331 -6.935000 5.13
## 279 105.7987 -6.935000 6.51
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## 281 105.9300 -6.935000 6.09
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## 283 106.0613 -6.935000 6.36
## 284 106.1269 -6.935000 6.07
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## 286 106.2581 -6.935000 5.52
## 287 106.3238 -6.935000 5.96
## 288 106.3894 -6.935000 5.83
## 289 106.4550 -6.935000 5.62
## 290 106.5206 -6.935000 5.74
## 291 106.5863 -6.935000 5.65
## 292 106.6519 -6.935000 5.89
## 293 106.7175 -6.935000 6.68
## 294 106.7831 -6.935000 4.26
## 295 106.8487 -6.935000 5.66
## 296 106.9144 -6.935000 5.91
## 297 106.9800 -6.935000 5.98
## 298 104.8800 -6.869375 5.58
## 299 104.9456 -6.869375 4.75
## 300 105.0113 -6.869375 6.00
## 301 105.0769 -6.869375 6.84
## 302 105.1425 -6.869375 4.88
## 303 105.2081 -6.869375 6.32
## 304 105.2738 -6.869375 5.60
## 305 105.3394 -6.869375 5.76
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## 309 105.6019 -6.869375 6.15
## 310 105.6675 -6.869375 6.84
## 311 105.7331 -6.869375 6.51
## 312 105.7987 -6.869375 6.06
## 313 105.8644 -6.869375 6.85
## 314 105.9300 -6.869375 6.06
## 315 105.9956 -6.869375 6.30
## 316 106.0613 -6.869375 5.62
## 317 106.1269 -6.869375 5.84
## 318 106.1925 -6.869375 5.38
## 319 106.2581 -6.869375 6.39
## 320 106.3238 -6.869375 5.09
## 321 106.3894 -6.869375 6.27
## 322 106.4550 -6.869375 5.69
## 323 106.5206 -6.869375 6.50
## 324 106.5863 -6.869375 6.25
## 325 106.6519 -6.869375 6.89
## 326 106.7175 -6.869375 6.24
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## 329 106.9144 -6.869375 5.10
## 330 106.9800 -6.869375 5.49
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## 332 104.9456 -6.803750 6.18
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## 334 105.0769 -6.803750 5.19
## 335 105.1425 -6.803750 5.82
## 336 105.2081 -6.803750 5.07
## 337 105.2738 -6.803750 5.40
## 338 105.3394 -6.803750 5.99
## 339 105.4050 -6.803750 6.49
## 340 105.4706 -6.803750 6.17
## 341 105.5362 -6.803750 4.43
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## 343 105.6675 -6.803750 5.84
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## 348 105.9956 -6.803750 6.15
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## 351 106.1925 -6.803750 6.02
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## 354 106.3894 -6.803750 6.29
## 355 106.4550 -6.803750 6.44
## 356 106.5206 -6.803750 5.94
## 357 106.5863 -6.803750 5.94
## 358 106.6519 -6.803750 5.96
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## 361 106.8487 -6.803750 5.71
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## 363 106.9800 -6.803750 6.40
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## 367 105.0769 -6.738125 5.35
## 368 105.1425 -6.738125 5.31
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## 370 105.2738 -6.738125 6.31
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## 372 105.4050 -6.738125 6.60
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## 374 105.5362 -6.738125 6.31
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## 378 105.7987 -6.738125 4.60
## 379 105.8644 -6.738125 6.76
## 380 105.9300 -6.738125 5.53
## 381 105.9956 -6.738125 5.86
## 382 106.0613 -6.738125 6.59
## 383 106.1269 -6.738125 4.84
## 384 106.1925 -6.738125 5.05
## 385 106.2581 -6.738125 4.84
## 386 106.3238 -6.738125 5.32
## 387 106.3894 -6.738125 6.06
## 388 106.4550 -6.738125 6.11
## 389 106.5206 -6.738125 5.97
## 390 106.5863 -6.738125 4.95
## 391 106.6519 -6.738125 4.41
## 392 106.7175 -6.738125 5.83
## 393 106.7831 -6.738125 5.52
## 394 106.8487 -6.738125 6.08
## 395 106.9144 -6.738125 6.22
## 396 106.9800 -6.738125 5.88
## 397 104.8800 -6.672500 6.26
## 398 104.9456 -6.672500 5.94
## 399 105.0113 -6.672500 6.12
## 400 105.0769 -6.672500 5.38
## 401 105.1425 -6.672500 5.69
## 402 105.2081 -6.672500 5.92
## 403 105.2738 -6.672500 6.29
## 404 105.3394 -6.672500 5.56
## 405 105.4050 -6.672500 6.11
## 406 105.4706 -6.672500 5.64
## 407 105.5362 -6.672500 5.73
## 408 105.6019 -6.672500 6.30
## 409 105.6675 -6.672500 4.60
## 410 105.7331 -6.672500 5.02
## 411 105.7987 -6.672500 4.91
## 412 105.8644 -6.672500 4.40
## 413 105.9300 -6.672500 5.39
## 414 105.9956 -6.672500 6.25
## 415 106.0613 -6.672500 5.63
## 416 106.1269 -6.672500 5.92
## 417 106.1925 -6.672500 6.45
## 418 106.2581 -6.672500 6.60
## 419 106.3238 -6.672500 5.76
## 420 106.3894 -6.672500 6.61
## 421 106.4550 -6.672500 5.86
## 422 106.5206 -6.672500 5.30
## 423 106.5863 -6.672500 5.44
## 424 106.6519 -6.672500 4.91
## 425 106.7175 -6.672500 5.27
## 426 106.7831 -6.672500 5.59
## 427 106.8487 -6.672500 6.28
## 428 106.9144 -6.672500 6.83
## 429 106.9800 -6.672500 4.97
## 430 104.8800 -6.606875 6.04
## 431 104.9456 -6.606875 5.18
## 432 105.0113 -6.606875 6.08
## 433 105.0769 -6.606875 5.72
## 434 105.1425 -6.606875 4.70
## 435 105.2081 -6.606875 6.36
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## 912 106.1925 -5.688125 6.04
## 913 106.2581 -5.688125 6.13
## 914 106.3238 -5.688125 5.43
## 915 106.3894 -5.688125 6.39
## 916 106.4550 -5.688125 6.49
## 917 106.5206 -5.688125 6.66
## 918 106.5863 -5.688125 6.12
## 919 106.6519 -5.688125 6.62
## 920 106.7175 -5.688125 4.67
## 921 106.7831 -5.688125 5.61
## 922 106.8487 -5.688125 5.28
## 923 106.9144 -5.688125 5.87
## 924 106.9800 -5.688125 5.46
## 925 104.8800 -5.622500 5.70
## 926 104.9456 -5.622500 6.93
## 927 105.0113 -5.622500 5.70
## 928 105.0769 -5.622500 6.05
## 929 105.1425 -5.622500 5.66
## 930 105.2081 -5.622500 5.85
## 931 105.2738 -5.622500 5.80
## 932 105.3394 -5.622500 6.07
## 933 105.4050 -5.622500 6.50
## 934 105.4706 -5.622500 6.79
## 935 105.5362 -5.622500 5.99
## 936 105.6019 -5.622500 6.15
## 937 105.6675 -5.622500 5.11
## 938 105.7331 -5.622500 5.75
## 939 105.7987 -5.622500 6.36
## 940 105.8644 -5.622500 6.32
## 941 105.9300 -5.622500 5.93
## 942 105.9956 -5.622500 6.33
## 943 106.0613 -5.622500 6.09
## 944 106.1269 -5.622500 6.52
## 945 106.1925 -5.622500 5.97
## 946 106.2581 -5.622500 5.59
## 947 106.3238 -5.622500 6.00
## 948 106.3894 -5.622500 4.04
## 949 106.4550 -5.622500 6.03
## 950 106.5206 -5.622500 4.00
## 951 106.5863 -5.622500 4.77
## 952 106.6519 -5.622500 6.07
## 953 106.7175 -5.622500 6.09
## 954 106.7831 -5.622500 5.10
## 955 106.8487 -5.622500 5.37
## 956 106.9144 -5.622500 6.62
## 957 106.9800 -5.622500 5.51
## 958 104.8800 -5.556875 7.15
## 959 104.9456 -5.556875 5.80
## 960 105.0113 -5.556875 6.04
## 961 105.0769 -5.556875 6.77
## 962 105.1425 -5.556875 5.88
## 963 105.2081 -5.556875 5.20
## 964 105.2738 -5.556875 5.73
## 965 105.3394 -5.556875 5.78
## 966 105.4050 -5.556875 4.98
## 967 105.4706 -5.556875 5.65
## 968 105.5362 -5.556875 5.35
## 969 105.6019 -5.556875 6.35
## 970 105.6675 -5.556875 5.82
## 971 105.7331 -5.556875 5.63
## 972 105.7987 -5.556875 5.74
## 973 105.8644 -5.556875 5.93
## 974 105.9300 -5.556875 6.17
## 975 105.9956 -5.556875 5.20
## 976 106.0613 -5.556875 5.18
## 977 106.1269 -5.556875 6.46
## 978 106.1925 -5.556875 5.55
## 979 106.2581 -5.556875 4.95
## 980 106.3238 -5.556875 6.07
## 981 106.3894 -5.556875 6.08
## 982 106.4550 -5.556875 4.88
## 983 106.5206 -5.556875 5.94
## 984 106.5863 -5.556875 6.24
## 985 106.6519 -5.556875 6.02
## 986 106.7175 -5.556875 6.18
## 987 106.7831 -5.556875 4.96
## 988 106.8487 -5.556875 6.00
## 989 106.9144 -5.556875 5.62
## 990 106.9800 -5.556875 5.51
## 991 104.8800 -5.491250 6.32
## 992 104.9456 -5.491250 6.69
## 993 105.0113 -5.491250 6.88
## 994 105.0769 -5.491250 6.59
## 995 105.1425 -5.491250 5.73
## 996 105.2081 -5.491250 6.01
## 997 105.2738 -5.491250 6.26
## 998 105.3394 -5.491250 5.87
## 999 105.4050 -5.491250 5.88
## 1000 105.4706 -5.491250 6.29
## 1001 105.5362 -5.491250 5.76
## 1002 105.6019 -5.491250 5.36
## 1003 105.6675 -5.491250 5.55
## 1004 105.7331 -5.491250 6.18
## 1005 105.7987 -5.491250 5.80
## 1006 105.8644 -5.491250 6.00
## 1007 105.9300 -5.491250 6.20
## 1008 105.9956 -5.491250 5.58
## 1009 106.0613 -5.491250 6.25
## 1010 106.1269 -5.491250 6.03
## 1011 106.1925 -5.491250 5.06
## 1012 106.2581 -5.491250 6.67
## 1013 106.3238 -5.491250 5.50
## 1014 106.3894 -5.491250 4.81
## 1015 106.4550 -5.491250 5.17
## 1016 106.5206 -5.491250 5.19
## 1017 106.5863 -5.491250 5.83
## 1018 106.6519 -5.491250 5.64
## 1019 106.7175 -5.491250 5.60
## 1020 106.7831 -5.491250 6.17
## 1021 106.8487 -5.491250 6.00
## 1022 106.9144 -5.491250 5.99
## 1023 106.9800 -5.491250 6.05
## 1024 104.8800 -5.425625 6.17
## 1025 104.9456 -5.425625 4.54
## 1026 105.0113 -5.425625 5.58
## 1027 105.0769 -5.425625 4.49
## 1028 105.1425 -5.425625 5.82
## 1029 105.2081 -5.425625 5.80
## 1030 105.2738 -5.425625 6.43
## 1031 105.3394 -5.425625 6.51
## 1032 105.4050 -5.425625 5.92
## 1033 105.4706 -5.425625 5.50
## 1034 105.5362 -5.425625 6.09
## 1035 105.6019 -5.425625 5.48
## 1036 105.6675 -5.425625 5.80
## 1037 105.7331 -5.425625 6.39
## 1038 105.7987 -5.425625 5.47
## 1039 105.8644 -5.425625 6.28
## 1040 105.9300 -5.425625 6.21
## 1041 105.9956 -5.425625 5.23
## 1042 106.0613 -5.425625 6.38
## 1043 106.1269 -5.425625 6.22
## 1044 106.1925 -5.425625 5.86
## 1045 106.2581 -5.425625 5.34
## 1046 106.3238 -5.425625 5.28
## 1047 106.3894 -5.425625 5.48
## 1048 106.4550 -5.425625 6.13
## 1049 106.5206 -5.425625 5.23
## 1050 106.5863 -5.425625 6.06
## 1051 106.6519 -5.425625 5.05
## 1052 106.7175 -5.425625 5.68
## 1053 106.7831 -5.425625 5.87
## 1054 106.8487 -5.425625 7.27
## 1055 106.9144 -5.425625 4.97
## 1056 106.9800 -5.425625 6.68
## 1057 104.8800 -5.360000 5.89
## 1058 104.9456 -5.360000 6.05
## 1059 105.0113 -5.360000 5.87
## 1060 105.0769 -5.360000 6.07
## 1061 105.1425 -5.360000 5.71
## 1062 105.2081 -5.360000 6.67
## 1063 105.2738 -5.360000 5.53
## 1064 105.3394 -5.360000 6.48
## 1065 105.4050 -5.360000 5.41
## 1066 105.4706 -5.360000 5.76
## 1067 105.5362 -5.360000 5.16
## 1068 105.6019 -5.360000 6.07
## 1069 105.6675 -5.360000 6.67
## 1070 105.7331 -5.360000 5.75
## 1071 105.7987 -5.360000 5.68
## 1072 105.8644 -5.360000 5.13
## 1073 105.9300 -5.360000 5.66
## 1074 105.9956 -5.360000 4.84
## 1075 106.0613 -5.360000 5.25
## 1076 106.1269 -5.360000 5.94
## 1077 106.1925 -5.360000 6.59
## 1078 106.2581 -5.360000 7.49
## 1079 106.3238 -5.360000 5.45
## 1080 106.3894 -5.360000 6.66
## 1081 106.4550 -5.360000 5.95
## 1082 106.5206 -5.360000 5.71
## 1083 106.5863 -5.360000 6.06
## 1084 106.6519 -5.360000 5.84
## 1085 106.7175 -5.360000 5.87
## 1086 106.7831 -5.360000 5.56
## 1087 106.8487 -5.360000 4.96
## 1088 106.9144 -5.360000 4.87
## 1089 106.9800 -5.360000 6.19
nrow(data)
## [1] 1089
# 2. Ubah menjadi data spasial berdasarkan koordinat
data_sf <- st_as_sf(data, coords = c("longitude", "latitude"), crs = 4326)
sum(is.na(data))
## [1] 0
# 3. Visualisasi peta spasial
tmap_mode("view") # mode interaktif (bisa di-zoom)
## ℹ tmap modes "plot" - "view"
## ℹ toggle with `tmap::ttm()`
tm_shape(data_sf) +
tm_dots(
col = "ph",
palette = "RdYlBu",
size = 0.6,
title = "Nilai pH"
) +
tm_layout(
title = "Peta Sebaran Nilai pH di Provinsi Banten",
legend.outside = TRUE
)
##
## ── tmap v3 code detected ───────────────────────────────────────────────────────
## [v3->v4] `tm_tm_dots()`: migrate the argument(s) related to the scale of the
## visual variable `fill` namely 'palette' (rename to 'values') to fill.scale =
## tm_scale(<HERE>).[v3->v4] `tm_dots()`: use 'fill' for the fill color of polygons/symbols
## (instead of 'col'), and 'col' for the outlines (instead of 'border.col').[tm_dots()] Argument `title` unknown.[v3->v4] `tm_layout()`: use `tm_title()` instead of `tm_layout(title = )`[cols4all] color palettes: use palettes from the R package cols4all. Run
## `cols4all::c4a_gui()` to explore them. The old palette name "RdYlBu" is named
## "brewer.rd_yl_bu"Multiple palettes called "rd_yl_bu" found: "brewer.rd_yl_bu", "matplotlib.rd_yl_bu". The first one, "brewer.rd_yl_bu", is returned.
## Registered S3 method overwritten by 'jsonify':
## method from
## print.json jsonlite
# ==========================================================
# INTERPOLASI pH TANAH PROVINSI BANTEN (IDW & KRIGING)
# ==========================================================
# --- 1. Install & load library (auto install kalau belum ada) ---
libs <- c("sf", "sp", "gstat", "raster", "ggplot2",
"rnaturalearth", "rnaturalearthdata", "viridis", "dplyr")
installed <- libs %in% installed.packages()
if (any(!installed)) install.packages(libs[!installed])
lapply(libs, library, character.only = TRUE)
##
## Attaching package: 'raster'
## The following object is masked from 'package:dplyr':
##
## select
## [[1]]
## [1] "dplyr" "viridis" "viridisLite"
## [4] "rnaturalearthdata" "rnaturalearth" "automap"
## [7] "gstat" "ggstats" "ggplot2"
## [10] "sp" "sf" "readr"
## [13] "tmap" "stats" "graphics"
## [16] "grDevices" "utils" "datasets"
## [19] "methods" "base"
##
## [[2]]
## [1] "dplyr" "viridis" "viridisLite"
## [4] "rnaturalearthdata" "rnaturalearth" "automap"
## [7] "gstat" "ggstats" "ggplot2"
## [10] "sp" "sf" "readr"
## [13] "tmap" "stats" "graphics"
## [16] "grDevices" "utils" "datasets"
## [19] "methods" "base"
##
## [[3]]
## [1] "dplyr" "viridis" "viridisLite"
## [4] "rnaturalearthdata" "rnaturalearth" "automap"
## [7] "gstat" "ggstats" "ggplot2"
## [10] "sp" "sf" "readr"
## [13] "tmap" "stats" "graphics"
## [16] "grDevices" "utils" "datasets"
## [19] "methods" "base"
##
## [[4]]
## [1] "raster" "dplyr" "viridis"
## [4] "viridisLite" "rnaturalearthdata" "rnaturalearth"
## [7] "automap" "gstat" "ggstats"
## [10] "ggplot2" "sp" "sf"
## [13] "readr" "tmap" "stats"
## [16] "graphics" "grDevices" "utils"
## [19] "datasets" "methods" "base"
##
## [[5]]
## [1] "raster" "dplyr" "viridis"
## [4] "viridisLite" "rnaturalearthdata" "rnaturalearth"
## [7] "automap" "gstat" "ggstats"
## [10] "ggplot2" "sp" "sf"
## [13] "readr" "tmap" "stats"
## [16] "graphics" "grDevices" "utils"
## [19] "datasets" "methods" "base"
##
## [[6]]
## [1] "raster" "dplyr" "viridis"
## [4] "viridisLite" "rnaturalearthdata" "rnaturalearth"
## [7] "automap" "gstat" "ggstats"
## [10] "ggplot2" "sp" "sf"
## [13] "readr" "tmap" "stats"
## [16] "graphics" "grDevices" "utils"
## [19] "datasets" "methods" "base"
##
## [[7]]
## [1] "raster" "dplyr" "viridis"
## [4] "viridisLite" "rnaturalearthdata" "rnaturalearth"
## [7] "automap" "gstat" "ggstats"
## [10] "ggplot2" "sp" "sf"
## [13] "readr" "tmap" "stats"
## [16] "graphics" "grDevices" "utils"
## [19] "datasets" "methods" "base"
##
## [[8]]
## [1] "raster" "dplyr" "viridis"
## [4] "viridisLite" "rnaturalearthdata" "rnaturalearth"
## [7] "automap" "gstat" "ggstats"
## [10] "ggplot2" "sp" "sf"
## [13] "readr" "tmap" "stats"
## [16] "graphics" "grDevices" "utils"
## [19] "datasets" "methods" "base"
##
## [[9]]
## [1] "raster" "dplyr" "viridis"
## [4] "viridisLite" "rnaturalearthdata" "rnaturalearth"
## [7] "automap" "gstat" "ggstats"
## [10] "ggplot2" "sp" "sf"
## [13] "readr" "tmap" "stats"
## [16] "graphics" "grDevices" "utils"
## [19] "datasets" "methods" "base"
# --- 2. Baca data CSV ---
print(data)
## longitude latitude ph
## 1 104.8800 -7.460000 5.98
## 2 104.9456 -7.460000 5.18
## 3 105.0113 -7.460000 6.25
## 4 105.0769 -7.460000 6.36
## 5 105.1425 -7.460000 4.63
## 6 105.2081 -7.460000 5.02
## 7 105.2738 -7.460000 5.88
## 8 105.3394 -7.460000 5.61
## 9 105.4050 -7.460000 5.79
## 10 105.4706 -7.460000 5.29
## 11 105.5362 -7.460000 6.33
## 12 105.6019 -7.460000 6.27
## 13 105.6675 -7.460000 5.84
## 14 105.7331 -7.460000 6.48
## 15 105.7987 -7.460000 6.08
## 16 105.8644 -7.460000 5.28
## 17 105.9300 -7.460000 6.02
## 18 105.9956 -7.460000 5.22
## 19 106.0613 -7.460000 6.33
## 20 106.1269 -7.460000 5.77
## 21 106.1925 -7.460000 5.69
## 22 106.2581 -7.460000 5.39
## 23 106.3238 -7.460000 6.53
## 24 106.3894 -7.460000 5.71
## 25 106.4550 -7.460000 5.54
## 26 106.5206 -7.460000 5.59
## 27 106.5863 -7.460000 6.12
## 28 106.6519 -7.460000 6.02
## 29 106.7175 -7.460000 6.05
## 30 106.7831 -7.460000 6.06
## 31 106.8487 -7.460000 7.08
## 32 106.9144 -7.460000 5.56
## 33 106.9800 -7.460000 5.49
## 34 104.8800 -7.394375 5.31
## 35 104.9456 -7.394375 6.17
## 36 105.0113 -7.394375 6.48
## 37 105.0769 -7.394375 5.73
## 38 105.1425 -7.394375 5.30
## 39 105.2081 -7.394375 5.31
## 40 105.2738 -7.394375 6.19
## 41 105.3394 -7.394375 6.25
## 42 105.4050 -7.394375 6.13
## 43 105.4706 -7.394375 5.40
## 44 105.5362 -7.394375 5.94
## 45 105.6019 -7.394375 5.87
## 46 105.6675 -7.394375 5.93
## 47 105.7331 -7.394375 6.32
## 48 105.7987 -7.394375 5.93
## 49 105.8644 -7.394375 6.21
## 50 105.9300 -7.394375 5.84
## 51 105.9956 -7.394375 5.97
## 52 106.0613 -7.394375 6.18
## 53 106.1269 -7.394375 4.93
## 54 106.1925 -7.394375 5.61
## 55 106.2581 -7.394375 5.52
## 56 106.3238 -7.394375 5.42
## 57 106.3894 -7.394375 5.63
## 58 106.4550 -7.394375 6.70
## 59 106.5206 -7.394375 5.28
## 60 106.5863 -7.394375 6.38
## 61 106.6519 -7.394375 4.79
## 62 106.7175 -7.394375 5.60
## 63 106.7831 -7.394375 5.90
## 64 106.8487 -7.394375 6.15
## 65 106.9144 -7.394375 6.23
## 66 106.9800 -7.394375 6.28
## 67 104.8800 -7.328750 5.59
## 68 104.9456 -7.328750 5.52
## 69 105.0113 -7.328750 6.31
## 70 105.0769 -7.328750 5.69
## 71 105.1425 -7.328750 5.03
## 72 105.2081 -7.328750 5.12
## 73 105.2738 -7.328750 5.25
## 74 105.3394 -7.328750 6.10
## 75 105.4050 -7.328750 5.89
## 76 105.4706 -7.328750 6.21
## 77 105.5362 -7.328750 5.54
## 78 105.6019 -7.328750 5.90
## 79 105.6675 -7.328750 6.18
## 80 105.7331 -7.328750 5.61
## 81 105.7987 -7.328750 6.07
## 82 105.8644 -7.328750 5.40
## 83 105.9300 -7.328750 5.58
## 84 105.9956 -7.328750 5.57
## 85 106.0613 -7.328750 5.08
## 86 106.1269 -7.328750 6.09
## 87 106.1925 -7.328750 5.52
## 88 106.2581 -7.328750 5.81
## 89 106.3238 -7.328750 6.09
## 90 106.3894 -7.328750 6.07
## 91 106.4550 -7.328750 6.20
## 92 106.5206 -7.328750 5.74
## 93 106.5863 -7.328750 5.55
## 94 106.6519 -7.328750 5.75
## 95 106.7175 -7.328750 4.79
## 96 106.7831 -7.328750 4.93
## 97 106.8487 -7.328750 5.01
## 98 106.9144 -7.328750 5.20
## 99 106.9800 -7.328750 6.04
## 100 104.8800 -7.263125 5.26
## 101 104.9456 -7.263125 5.57
## 102 105.0113 -7.263125 6.58
## 103 105.0769 -7.263125 5.59
## 104 105.1425 -7.263125 6.24
## 105 105.2081 -7.263125 5.24
## 106 105.2738 -7.263125 5.68
## 107 105.3394 -7.263125 5.23
## 108 105.4050 -7.263125 5.60
## 109 105.4706 -7.263125 6.30
## 110 105.5362 -7.263125 4.76
## 111 105.6019 -7.263125 6.06
## 112 105.6675 -7.263125 5.94
## 113 105.7331 -7.263125 5.44
## 114 105.7987 -7.263125 4.93
## 115 105.8644 -7.263125 5.84
## 116 105.9300 -7.263125 5.48
## 117 105.9956 -7.263125 5.94
## 118 106.0613 -7.263125 5.81
## 119 106.1269 -7.263125 6.76
## 120 106.1925 -7.263125 5.66
## 121 106.2581 -7.263125 5.19
## 122 106.3238 -7.263125 5.91
## 123 106.3894 -7.263125 5.93
## 124 106.4550 -7.263125 6.62
## 125 106.5206 -7.263125 6.30
## 126 106.5863 -7.263125 6.01
## 127 106.6519 -7.263125 6.68
## 128 106.7175 -7.263125 5.09
## 129 106.7831 -7.263125 5.42
## 130 106.8487 -7.263125 5.24
## 131 106.9144 -7.263125 5.57
## 132 106.9800 -7.263125 4.97
## 133 104.8800 -7.197500 6.18
## 134 104.9456 -7.197500 5.67
## 135 105.0113 -7.197500 4.92
## 136 105.0769 -7.197500 5.19
## 137 105.1425 -7.197500 5.99
## 138 105.2081 -7.197500 6.30
## 139 105.2738 -7.197500 7.00
## 140 105.3394 -7.197500 7.55
## 141 105.4050 -7.197500 6.05
## 142 105.4706 -7.197500 5.21
## 143 105.5362 -7.197500 4.52
## 144 105.6019 -7.197500 5.96
## 145 105.6675 -7.197500 5.31
## 146 105.7331 -7.197500 5.55
## 147 105.7987 -7.197500 5.43
## 148 105.8644 -7.197500 5.72
## 149 105.9300 -7.197500 6.44
## 150 105.9956 -7.197500 5.89
## 151 106.0613 -7.197500 5.70
## 152 106.1269 -7.197500 5.18
## 153 106.1925 -7.197500 4.80
## 154 106.2581 -7.197500 5.51
## 155 106.3238 -7.197500 5.77
## 156 106.3894 -7.197500 6.86
## 157 106.4550 -7.197500 5.88
## 158 106.5206 -7.197500 6.39
## 159 106.5863 -7.197500 5.50
## 160 106.6519 -7.197500 5.09
## 161 106.7175 -7.197500 5.22
## 162 106.7831 -7.197500 5.36
## 163 106.8487 -7.197500 7.08
## 164 106.9144 -7.197500 5.31
## 165 106.9800 -7.197500 6.30
## 166 104.8800 -7.131875 5.26
## 167 104.9456 -7.131875 6.36
## 168 105.0113 -7.131875 6.03
## 169 105.0769 -7.131875 5.71
## 170 105.1425 -7.131875 5.78
## 171 105.2081 -7.131875 5.41
## 172 105.2738 -7.131875 6.07
## 173 105.3394 -7.131875 5.53
## 174 105.4050 -7.131875 5.06
## 175 105.4706 -7.131875 5.03
## 176 105.5362 -7.131875 5.90
## 177 105.6019 -7.131875 6.75
## 178 105.6675 -7.131875 5.90
## 179 105.7331 -7.131875 5.73
## 180 105.7987 -7.131875 5.97
## 181 105.8644 -7.131875 6.58
## 182 105.9300 -7.131875 5.93
## 183 105.9956 -7.131875 5.55
## 184 106.0613 -7.131875 6.46
## 185 106.1269 -7.131875 6.06
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## 675 105.7987 -6.147500 6.30
## 676 105.8644 -6.147500 6.01
## 677 105.9300 -6.147500 7.23
## 678 105.9956 -6.147500 6.05
## 679 106.0613 -6.147500 6.03
## 680 106.1269 -6.147500 5.70
## 681 106.1925 -6.147500 6.29
## 682 106.2581 -6.147500 6.18
## 683 106.3238 -6.147500 6.55
## 684 106.3894 -6.147500 5.49
## 685 106.4550 -6.147500 5.54
## 686 106.5206 -6.147500 5.51
## 687 106.5863 -6.147500 6.27
## 688 106.6519 -6.147500 6.70
## 689 106.7175 -6.147500 5.52
## 690 106.7831 -6.147500 5.55
## 691 106.8487 -6.147500 5.99
## 692 106.9144 -6.147500 5.65
## 693 106.9800 -6.147500 6.37
## 694 104.8800 -6.081875 4.45
## 695 104.9456 -6.081875 5.30
## 696 105.0113 -6.081875 5.33
## 697 105.0769 -6.081875 4.41
## 698 105.1425 -6.081875 5.22
## 699 105.2081 -6.081875 5.25
## 700 105.2738 -6.081875 5.68
## 701 105.3394 -6.081875 6.47
## 702 105.4050 -6.081875 5.65
## 703 105.4706 -6.081875 5.18
## 704 105.5362 -6.081875 5.77
## 705 105.6019 -6.081875 6.43
## 706 105.6675 -6.081875 5.21
## 707 105.7331 -6.081875 5.25
## 708 105.7987 -6.081875 6.14
## 709 105.8644 -6.081875 5.67
## 710 105.9300 -6.081875 6.19
## 711 105.9956 -6.081875 5.79
## 712 106.0613 -6.081875 6.22
## 713 106.1269 -6.081875 5.18
## 714 106.1925 -6.081875 5.79
## 715 106.2581 -6.081875 5.67
## 716 106.3238 -6.081875 5.07
## 717 106.3894 -6.081875 4.86
## 718 106.4550 -6.081875 6.21
## 719 106.5206 -6.081875 5.59
## 720 106.5863 -6.081875 5.19
## 721 106.6519 -6.081875 5.74
## 722 106.7175 -6.081875 6.48
## 723 106.7831 -6.081875 4.43
## 724 106.8487 -6.081875 4.90
## 725 106.9144 -6.081875 5.25
## 726 106.9800 -6.081875 6.68
## 727 104.8800 -6.016250 5.97
## 728 104.9456 -6.016250 6.26
## 729 105.0113 -6.016250 5.12
## 730 105.0769 -6.016250 5.13
## 731 105.1425 -6.016250 6.07
## 732 105.2081 -6.016250 5.83
## 733 105.2738 -6.016250 6.13
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## 735 105.4050 -6.016250 5.97
## 736 105.4706 -6.016250 5.89
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## 740 105.7331 -6.016250 4.45
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## 742 105.8644 -6.016250 6.51
## 743 105.9300 -6.016250 5.19
## 744 105.9956 -6.016250 4.68
## 745 106.0613 -6.016250 5.86
## 746 106.1269 -6.016250 6.36
## 747 106.1925 -6.016250 6.88
## 748 106.2581 -6.016250 6.11
## 749 106.3238 -6.016250 5.58
## 750 106.3894 -6.016250 5.26
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## 752 106.5206 -6.016250 5.62
## 753 106.5863 -6.016250 5.19
## 754 106.6519 -6.016250 7.03
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## 756 106.7831 -6.016250 6.48
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## 761 104.9456 -5.950625 6.55
## 762 105.0113 -5.950625 6.18
## 763 105.0769 -5.950625 6.24
## 764 105.1425 -5.950625 6.18
## 765 105.2081 -5.950625 6.00
## 766 105.2738 -5.950625 4.73
## 767 105.3394 -5.950625 5.85
## 768 105.4050 -5.950625 5.47
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## 770 105.5362 -5.950625 6.81
## 771 105.6019 -5.950625 6.84
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## 776 105.9300 -5.950625 5.92
## 777 105.9956 -5.950625 5.14
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## 779 106.1269 -5.950625 5.84
## 780 106.1925 -5.950625 5.02
## 781 106.2581 -5.950625 5.77
## 782 106.3238 -5.950625 5.75
## 783 106.3894 -5.950625 6.88
## 784 106.4550 -5.950625 6.34
## 785 106.5206 -5.950625 5.81
## 786 106.5863 -5.950625 5.95
## 787 106.6519 -5.950625 5.83
## 788 106.7175 -5.950625 5.68
## 789 106.7831 -5.950625 5.15
## 790 106.8487 -5.950625 5.71
## 791 106.9144 -5.950625 5.35
## 792 106.9800 -5.950625 5.05
## 793 104.8800 -5.885000 6.11
## 794 104.9456 -5.885000 6.03
## 795 105.0113 -5.885000 4.73
## 796 105.0769 -5.885000 5.73
## 797 105.1425 -5.885000 6.40
## 798 105.2081 -5.885000 6.44
## 799 105.2738 -5.885000 6.42
## 800 105.3394 -5.885000 5.82
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## 803 105.5362 -5.885000 6.01
## 804 105.6019 -5.885000 6.03
## 805 105.6675 -5.885000 6.57
## 806 105.7331 -5.885000 6.46
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## 808 105.8644 -5.885000 5.05
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## 810 105.9956 -5.885000 5.93
## 811 106.0613 -5.885000 5.68
## 812 106.1269 -5.885000 5.45
## 813 106.1925 -5.885000 5.95
## 814 106.2581 -5.885000 5.50
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## 818 106.5206 -5.885000 5.95
## 819 106.5863 -5.885000 5.96
## 820 106.6519 -5.885000 5.12
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## 825 106.9800 -5.885000 4.68
## 826 104.8800 -5.819375 5.82
## 827 104.9456 -5.819375 5.82
## 828 105.0113 -5.819375 5.73
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## 830 105.1425 -5.819375 4.20
## 831 105.2081 -5.819375 6.04
## 832 105.2738 -5.819375 6.74
## 833 105.3394 -5.819375 5.12
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## 835 105.4706 -5.819375 5.35
## 836 105.5362 -5.819375 5.26
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## 896 105.1425 -5.688125 6.43
## 897 105.2081 -5.688125 5.39
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## 922 106.8487 -5.688125 5.28
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## 927 105.0113 -5.622500 5.70
## 928 105.0769 -5.622500 6.05
## 929 105.1425 -5.622500 5.66
## 930 105.2081 -5.622500 5.85
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## 933 105.4050 -5.622500 6.50
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## 936 105.6019 -5.622500 6.15
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## 940 105.8644 -5.622500 6.32
## 941 105.9300 -5.622500 5.93
## 942 105.9956 -5.622500 6.33
## 943 106.0613 -5.622500 6.09
## 944 106.1269 -5.622500 6.52
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## 947 106.3238 -5.622500 6.00
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## 949 106.4550 -5.622500 6.03
## 950 106.5206 -5.622500 4.00
## 951 106.5863 -5.622500 4.77
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## 957 106.9800 -5.622500 5.51
## 958 104.8800 -5.556875 7.15
## 959 104.9456 -5.556875 5.80
## 960 105.0113 -5.556875 6.04
## 961 105.0769 -5.556875 6.77
## 962 105.1425 -5.556875 5.88
## 963 105.2081 -5.556875 5.20
## 964 105.2738 -5.556875 5.73
## 965 105.3394 -5.556875 5.78
## 966 105.4050 -5.556875 4.98
## 967 105.4706 -5.556875 5.65
## 968 105.5362 -5.556875 5.35
## 969 105.6019 -5.556875 6.35
## 970 105.6675 -5.556875 5.82
## 971 105.7331 -5.556875 5.63
## 972 105.7987 -5.556875 5.74
## 973 105.8644 -5.556875 5.93
## 974 105.9300 -5.556875 6.17
## 975 105.9956 -5.556875 5.20
## 976 106.0613 -5.556875 5.18
## 977 106.1269 -5.556875 6.46
## 978 106.1925 -5.556875 5.55
## 979 106.2581 -5.556875 4.95
## 980 106.3238 -5.556875 6.07
## 981 106.3894 -5.556875 6.08
## 982 106.4550 -5.556875 4.88
## 983 106.5206 -5.556875 5.94
## 984 106.5863 -5.556875 6.24
## 985 106.6519 -5.556875 6.02
## 986 106.7175 -5.556875 6.18
## 987 106.7831 -5.556875 4.96
## 988 106.8487 -5.556875 6.00
## 989 106.9144 -5.556875 5.62
## 990 106.9800 -5.556875 5.51
## 991 104.8800 -5.491250 6.32
## 992 104.9456 -5.491250 6.69
## 993 105.0113 -5.491250 6.88
## 994 105.0769 -5.491250 6.59
## 995 105.1425 -5.491250 5.73
## 996 105.2081 -5.491250 6.01
## 997 105.2738 -5.491250 6.26
## 998 105.3394 -5.491250 5.87
## 999 105.4050 -5.491250 5.88
## 1000 105.4706 -5.491250 6.29
## 1001 105.5362 -5.491250 5.76
## 1002 105.6019 -5.491250 5.36
## 1003 105.6675 -5.491250 5.55
## 1004 105.7331 -5.491250 6.18
## 1005 105.7987 -5.491250 5.80
## 1006 105.8644 -5.491250 6.00
## 1007 105.9300 -5.491250 6.20
## 1008 105.9956 -5.491250 5.58
## 1009 106.0613 -5.491250 6.25
## 1010 106.1269 -5.491250 6.03
## 1011 106.1925 -5.491250 5.06
## 1012 106.2581 -5.491250 6.67
## 1013 106.3238 -5.491250 5.50
## 1014 106.3894 -5.491250 4.81
## 1015 106.4550 -5.491250 5.17
## 1016 106.5206 -5.491250 5.19
## 1017 106.5863 -5.491250 5.83
## 1018 106.6519 -5.491250 5.64
## 1019 106.7175 -5.491250 5.60
## 1020 106.7831 -5.491250 6.17
## 1021 106.8487 -5.491250 6.00
## 1022 106.9144 -5.491250 5.99
## 1023 106.9800 -5.491250 6.05
## 1024 104.8800 -5.425625 6.17
## 1025 104.9456 -5.425625 4.54
## 1026 105.0113 -5.425625 5.58
## 1027 105.0769 -5.425625 4.49
## 1028 105.1425 -5.425625 5.82
## 1029 105.2081 -5.425625 5.80
## 1030 105.2738 -5.425625 6.43
## 1031 105.3394 -5.425625 6.51
## 1032 105.4050 -5.425625 5.92
## 1033 105.4706 -5.425625 5.50
## 1034 105.5362 -5.425625 6.09
## 1035 105.6019 -5.425625 5.48
## 1036 105.6675 -5.425625 5.80
## 1037 105.7331 -5.425625 6.39
## 1038 105.7987 -5.425625 5.47
## 1039 105.8644 -5.425625 6.28
## 1040 105.9300 -5.425625 6.21
## 1041 105.9956 -5.425625 5.23
## 1042 106.0613 -5.425625 6.38
## 1043 106.1269 -5.425625 6.22
## 1044 106.1925 -5.425625 5.86
## 1045 106.2581 -5.425625 5.34
## 1046 106.3238 -5.425625 5.28
## 1047 106.3894 -5.425625 5.48
## 1048 106.4550 -5.425625 6.13
## 1049 106.5206 -5.425625 5.23
## 1050 106.5863 -5.425625 6.06
## 1051 106.6519 -5.425625 5.05
## 1052 106.7175 -5.425625 5.68
## 1053 106.7831 -5.425625 5.87
## 1054 106.8487 -5.425625 7.27
## 1055 106.9144 -5.425625 4.97
## 1056 106.9800 -5.425625 6.68
## 1057 104.8800 -5.360000 5.89
## 1058 104.9456 -5.360000 6.05
## 1059 105.0113 -5.360000 5.87
## 1060 105.0769 -5.360000 6.07
## 1061 105.1425 -5.360000 5.71
## 1062 105.2081 -5.360000 6.67
## 1063 105.2738 -5.360000 5.53
## 1064 105.3394 -5.360000 6.48
## 1065 105.4050 -5.360000 5.41
## 1066 105.4706 -5.360000 5.76
## 1067 105.5362 -5.360000 5.16
## 1068 105.6019 -5.360000 6.07
## 1069 105.6675 -5.360000 6.67
## 1070 105.7331 -5.360000 5.75
## 1071 105.7987 -5.360000 5.68
## 1072 105.8644 -5.360000 5.13
## 1073 105.9300 -5.360000 5.66
## 1074 105.9956 -5.360000 4.84
## 1075 106.0613 -5.360000 5.25
## 1076 106.1269 -5.360000 5.94
## 1077 106.1925 -5.360000 6.59
## 1078 106.2581 -5.360000 7.49
## 1079 106.3238 -5.360000 5.45
## 1080 106.3894 -5.360000 6.66
## 1081 106.4550 -5.360000 5.95
## 1082 106.5206 -5.360000 5.71
## 1083 106.5863 -5.360000 6.06
## 1084 106.6519 -5.360000 5.84
## 1085 106.7175 -5.360000 5.87
## 1086 106.7831 -5.360000 5.56
## 1087 106.8487 -5.360000 4.96
## 1088 106.9144 -5.360000 4.87
## 1089 106.9800 -5.360000 6.19
head(data)
## longitude latitude ph
## 1 104.8800 -7.46 5.98
## 2 104.9456 -7.46 5.18
## 3 105.0113 -7.46 6.25
## 4 105.0769 -7.46 6.36
## 5 105.1425 -7.46 4.63
## 6 105.2081 -7.46 5.02
# --- 3. Konversi ke objek spasial ---
ph_sf <- st_as_sf(data, coords = c("longitude", "latitude"), crs = 4326)
ph_utm <- st_transform(ph_sf, crs = 32748) # UTM zona 48S (Banten)
ph_sp <- as(ph_utm, "Spatial")
# --- 4. Buat grid (tanpa xlim/ylim) ---
grid <- st_make_grid(ph_utm, cellsize = 1000, what = "centers")
grid_sf <- st_sf(geometry = grid)
grid_sp <- as(grid_sf, "Spatial")
# --- 5. Interpolasi IDW ---
idw_model <- gstat::idw(ph ~ 1, locations = ph_sp, newdata = grid_sp)
## [inverse distance weighted interpolation]
idw_df <- as.data.frame(idw_model)
names(idw_df)[1:3] <- c("x", "y", "pH")
# --- 6. Ambil batas Banten (Natural Earth) ---
banten <- ne_states(country = "indonesia", returnclass = "sf") %>%
filter(name == "Banten")
# --- 7. Plot hasil IDW ---
ggplot() +
geom_raster(data = idw_df, aes(x = x, y = y, fill = pH)) +
geom_sf(data = st_transform(banten, 32748), fill = NA, color = "black", size = 0.4) +
scale_fill_viridis(name = "ph", option = "plasma") +
coord_sf(crs = st_crs(32748)) +
labs(title = "Interpolasi pH Tanah - IDW (Banten)",
x = "Koordinat X (meter)", y = "Koordinat Y (meter)") +
theme_minimal()
# Variogram
vgm_model <- variogram(ph ~ 1, data = ph_sp)
fit_vgm <- fit.variogram(vgm_model, model = vgm("Sph"))
# Prediksi Kriging
kriging_ok <- krige(ph ~ 1, ph_sp, grid_sp, model = fit_vgm)
## [using ordinary kriging]
# Ubah ke dataframe
kriging_ok_df <- as.data.frame(kriging_ok)
names(kriging_ok_df)[1:3] <- c("x", "y", "pH")
ggplot() +
geom_raster(data = kriging_ok_df, aes(x = x, y = y, fill = pH)) +
geom_sf(data = st_transform(banten, 32748), fill = NA, color = "black", size = 0.4) +
scale_fill_viridis(name = "pH", option = "magma") +
coord_sf(crs = st_crs(32748)) +
labs(title = "Interpolasi pH Tanah - Ordinary Kriging (Banten)",
x = "Koordinat X (meter)", y = "Koordinat Y (meter)") +
theme_minimal()
library(sp)
library(gstat)
library(ggplot2)
library(viridis)
library(sf)
# --- 1. Pastikan ph_sp adalah SpatialPointsDataFrame ---
class(ph_sp) # harus "SpatialPointsDataFrame"
## [1] "SpatialPointsDataFrame"
## attr(,"package")
## [1] "sp"
# kalau masih sf:
# ph_sp <- as(ph_sf, "Spatial")
# --- 2. Tambahkan kolom koordinat X dan Y ke dalam data ---
ph_sp@data$x <- coordinates(ph_sp)[,1]
ph_sp@data$y <- coordinates(ph_sp)[,2]
# pastikan jumlahnya sama:
nrow(ph_sp@data) == nrow(coordinates(ph_sp)) # harus TRUE
## [1] TRUE
# --- 3. Pastikan grid_sp juga punya kolom x dan y ---
grid_sp@data$x <- coordinates(grid_sp)[,1]
grid_sp@data$y <- coordinates(grid_sp)[,2]
# --- 4. Buat variogram dengan tren spasial ---
vgm_model_uk <- variogram(ph ~ x + y, data = ph_sp)
# --- 5. Fit model variogram ---
fit_vgm_uk <- fit.variogram(vgm_model_uk, model = vgm("Sph"))
# --- 6. Jalankan Universal Kriging ---
kriging_uk <- krige(formula = ph ~ x + y,
locations = ph_sp,
newdata = grid_sp,
model = fit_vgm_uk)
## [using universal kriging]
# --- 7. Ubah hasil ke dataframe dan rename kolom ---
kriging_uk_df <- as.data.frame(kriging_uk)
names(kriging_uk_df)[1:3] <- c("x", "y", "pH")
# --- 8. Plot hasil ---
ggplot() +
geom_raster(data = kriging_uk_df, aes(x = x, y = y, fill = pH)) +
geom_sf(data = st_transform(banten, 32748), fill = NA, color = "black", size = 0.4) +
scale_fill_viridis(name = "pH", option = "inferno") +
coord_sf(crs = st_crs(32748)) +
labs(title = "Interpolasi pH Tanah - Universal Kriging (Banten)",
x = "Koordinat X (meter)", y = "Koordinat Y (meter)") +
theme_minimal()
