library(dbscan)
## Warning: package 'dbscan' was built under R version 4.5.3
##
## Attaching package: 'dbscan'
## The following object is masked from 'package:stats':
##
## as.dendrogram
data <- read.csv("C:/Semester 5/Pembelajaran Mesin Statistika/two_moons_X_only.csv")
summary(data)
## x y
## Min. :-1.17104 Min. :-0.6855
## 1st Qu.:-0.06955 1st Qu.:-0.2025
## Median : 0.50623 Median : 0.2513
## Mean : 0.49937 Mean : 0.2506
## 3rd Qu.: 1.05163 3rd Qu.: 0.6979
## Max. : 2.20284 Max. : 1.2222
M <- as.matrix(data[, c("x", "y")])
#DBSCAN
h <- dbscan(M, eps = 0.15, minPts = 5)
#menentukan cluster
data$cluster <- h$cluster
#menentukan core point
data$core <- is.corepoint(M, eps = 0.15, minPts = 5)
#jenis titik
data$jenis <- ifelse(data$core, "Core",
ifelse(data$cluster > 0, "Border", "Noise"))
print(data)
## x y cluster core jenis
## 1 1.8024007331 0.1695354869 1 TRUE Core
## 2 0.4071627466 0.9234600342 2 TRUE Core
## 3 0.4962463537 -0.3278621376 1 TRUE Core
## 4 -0.9504802266 0.1886795853 2 TRUE Core
## 5 0.4650315918 -0.3282850941 1 TRUE Core
## 6 0.2219100227 -0.2911209649 1 TRUE Core
## 7 -0.8615963903 0.2586723844 2 TRUE Core
## 8 1.6374907888 -0.2744428047 1 TRUE Core
## 9 0.9534505347 0.3691272907 2 TRUE Core
## 10 0.5035723140 -0.3154727894 1 TRUE Core
## 11 1.0669561731 0.1942995760 2 TRUE Core
## 12 0.3720756791 -0.3102562918 1 TRUE Core
## 13 0.0623352837 0.1344010073 1 TRUE Core
## 14 -0.2044036510 0.9690566396 2 TRUE Core
## 15 0.4431097473 0.9166682728 2 TRUE Core
## 16 0.6550810196 0.6011112709 2 TRUE Core
## 17 -0.6265368507 0.7420157145 2 TRUE Core
## 18 0.9999150434 0.1600436225 2 TRUE Core
## 19 1.6116488191 -0.4069068939 1 TRUE Core
## 20 1.9836942002 -0.0291791999 1 TRUE Core
## 21 -0.4726049475 0.7689004881 2 TRUE Core
## 22 1.4446417848 -0.2160304833 1 TRUE Core
## 23 1.9831437572 0.4608195807 1 TRUE Core
## 24 0.1034764112 0.2815949816 1 TRUE Core
## 25 1.9828594339 0.2894114967 1 TRUE Core
## 26 1.1442005523 0.3017145158 2 TRUE Core
## 27 0.1703810787 0.0504045913 1 TRUE Core
## 28 -0.9055067968 0.2048061360 2 TRUE Core
## 29 -0.7444036473 0.5145104832 2 TRUE Core
## 30 1.1265189225 -0.0006366088 2 TRUE Core
## 31 -0.3689794266 0.8591150634 2 TRUE Core
## 32 -0.9902106422 0.1984004756 2 TRUE Core
## 33 -0.2003147889 1.0078755408 2 TRUE Core
## 34 -0.8293423868 0.3215793102 2 TRUE Core
## 35 0.0119469039 0.3281934190 1 TRUE Core
## 36 0.2501942388 0.8897001017 2 TRUE Core
## 37 1.3853757304 -0.3852016861 1 TRUE Core
## 38 0.3640087216 -0.1806570939 1 TRUE Core
## 39 0.0179284928 0.2672089309 1 TRUE Core
## 40 0.6837475866 0.7177402473 2 TRUE Core
## 41 0.8372270357 0.2649357275 2 TRUE Core
## 42 2.1020364732 0.2077516835 1 TRUE Core
## 43 0.6250103558 0.5376096832 2 TRUE Core
## 44 -0.3167640109 0.8582231633 2 TRUE Core
## 45 1.3451135905 -0.3961025082 1 TRUE Core
## 46 -0.9074045167 0.7031625826 2 TRUE Core
## 47 0.0549578951 0.9737353636 2 TRUE Core
## 48 -1.1407159933 0.5223387763 2 TRUE Core
## 49 0.8647029207 0.0867261665 2 TRUE Core
## 50 1.4164275679 -0.2471722690 1 TRUE Core
## 51 1.2127679524 -0.4496689899 1 TRUE Core
## 52 0.7607756899 0.7692385815 2 TRUE Core
## 53 0.9056776875 -0.4654134130 1 TRUE Core
## 54 0.7942124284 0.6133762317 2 TRUE Core
## 55 -1.0205318525 0.2568088771 2 TRUE Core
## 56 1.5530890948 -0.2330791689 1 TRUE Core
## 57 0.2011361498 -0.2824929515 1 TRUE Core
## 58 1.5937496027 -0.2037129586 1 TRUE Core
## 59 0.2328305904 -0.1672425198 1 TRUE Core
## 60 0.3427353553 0.9819014578 2 TRUE Core
## 61 0.8381618924 -0.5145002550 1 TRUE Core
## 62 -0.4883131704 0.7690773339 2 TRUE Core
## 63 1.3812865183 -0.5346110669 1 TRUE Core
## 64 -0.0091975559 0.2493406704 1 TRUE Core
## 65 1.8718485509 0.4975100864 1 TRUE Core
## 66 1.8863456442 0.0841948590 1 TRUE Core
## 67 -0.9813749189 0.1468591271 2 TRUE Core
## 68 1.0493170549 -0.5335799355 1 TRUE Core
## 69 0.9494764210 0.3854839856 2 TRUE Core
## 70 0.9646097110 -0.4959801569 1 TRUE Core
## 71 0.7981309670 -0.5423594631 1 TRUE Core
## 72 0.2460127301 1.0736029031 2 TRUE Core
## 73 0.5777489726 -0.5019194056 1 TRUE Core
## 74 -0.0430884916 0.4025931298 1 TRUE Core
## 75 -0.7433725359 0.7940251720 2 TRUE Core
## 76 0.4704280336 0.8738486707 2 TRUE Core
## 77 1.3118572351 -0.2539136887 1 TRUE Core
## 78 -0.8808842136 0.6431693387 2 TRUE Core
## 79 0.4525491416 0.9488107563 2 TRUE Core
## 80 1.8292014713 -0.0466902992 1 TRUE Core
## 81 0.9800554881 0.2035279806 2 TRUE Core
## 82 -0.8248308722 0.6087006931 2 TRUE Core
## 83 0.9035357709 -0.6082383494 1 TRUE Core
## 84 1.1665856138 -0.2784310060 1 TRUE Core
## 85 1.5021770612 -0.1929523117 1 TRUE Core
## 86 1.0541111794 -0.5410734995 1 TRUE Core
## 87 1.8523117692 0.0394376948 1 TRUE Core
## 88 0.0372301333 0.9814287604 2 TRUE Core
## 89 0.5877828419 0.6918922549 2 TRUE Core
## 90 1.3954513024 -0.4922524345 1 TRUE Core
## 91 1.1794709532 -0.5458546649 1 TRUE Core
## 92 1.6793775963 -0.3751439569 1 TRUE Core
## 93 0.8162204980 0.6801110512 2 TRUE Core
## 94 0.4351343249 0.8339216560 2 TRUE Core
## 95 2.0335296567 0.0494155994 1 TRUE Core
## 96 2.0006163082 0.0348838495 1 TRUE Core
## 97 -0.5150085854 0.8841773404 2 TRUE Core
## 98 0.3013109403 -0.1628164424 1 TRUE Core
## 99 1.0509622419 -0.5736229833 1 TRUE Core
## 100 1.9907716311 0.1746867541 1 TRUE Core
## 101 -0.9750270921 0.1857469581 2 TRUE Core
## 102 -1.0586643920 0.1177547588 2 TRUE Core
## 103 0.3071970308 1.0242552222 2 TRUE Core
## 104 0.5165352128 -0.4435287829 1 TRUE Core
## 105 0.8276504278 0.6941402703 2 TRUE Core
## 106 -0.7440911379 0.3999408220 2 TRUE Core
## 107 -0.3545727423 0.9043276558 2 TRUE Core
## 108 0.7037564667 0.7086696320 2 TRUE Core
## 109 -0.2868485690 1.0156898630 2 TRUE Core
## 110 -0.2023636642 0.8837256172 2 TRUE Core
## 111 -0.9006768447 0.6977656914 2 TRUE Core
## 112 0.6612745540 -0.6403592003 1 TRUE Core
## 113 0.0393867980 0.5708626661 1 TRUE Core
## 114 1.7892644065 -0.0463494723 1 TRUE Core
## 115 -0.7219054182 0.6771859182 2 TRUE Core
## 116 0.4346815368 0.9092836739 2 TRUE Core
## 117 0.0733925231 0.2074621096 1 TRUE Core
## 118 -1.0501064899 0.1610354898 2 TRUE Core
## 119 0.4333967255 0.8338776004 2 TRUE Core
## 120 1.3686376083 -0.5173448111 1 TRUE Core
## 121 1.8562473605 -0.0210142317 1 TRUE Core
## 122 0.0932731176 0.4250069872 1 TRUE Core
## 123 0.0540774246 0.2352482535 1 TRUE Core
## 124 0.1285117972 1.0444752515 2 TRUE Core
## 125 0.3295166615 0.8394915068 2 TRUE Core
## 126 1.0605006049 -0.5137453660 1 TRUE Core
## 127 0.0626454530 0.9788172238 2 TRUE Core
## 128 -0.9329909280 0.3902989330 2 TRUE Core
## 129 0.1729597040 -0.0314318591 1 TRUE Core
## 130 0.4127562733 0.7551240019 2 TRUE Core
## 131 1.8698072256 0.1612699547 1 TRUE Core
## 132 1.8257443054 0.1620447394 1 TRUE Core
## 133 -0.5728766351 0.8161850730 2 TRUE Core
## 134 -0.1097121737 1.1149580627 2 TRUE Core
## 135 -0.8022677732 0.5536720717 2 TRUE Core
## 136 0.1869085265 -0.1693910109 1 TRUE Core
## 137 1.9667660401 0.4476418042 1 TRUE Core
## 138 1.9694718964 0.2089247183 1 TRUE Core
## 139 1.6219768006 -0.2143194614 1 TRUE Core
## 140 1.2154488382 -0.6090160910 1 TRUE Core
## 141 0.2422423747 -0.2581408407 1 TRUE Core
## 142 0.4622925334 0.8025213430 2 TRUE Core
## 143 1.4063909579 -0.5101838388 1 TRUE Core
## 144 -0.8653028238 0.4783566250 2 TRUE Core
## 145 1.1614832468 -0.6854963185 1 TRUE Core
## 146 -0.1394670516 1.0267480510 2 TRUE Core
## 147 -0.5852836368 0.8989415766 2 TRUE Core
## 148 0.3125335742 -0.1810303216 1 TRUE Core
## 149 0.7529216422 0.5910513585 2 TRUE Core
## 150 1.0253632212 0.3557930290 2 TRUE Core
## 151 1.5797340295 -0.3879086219 1 TRUE Core
## 152 -1.0231263112 0.0858055470 2 TRUE Core
## 153 -0.3749911030 1.0694423159 2 TRUE Core
## 154 0.0428670659 -0.1600705120 1 TRUE Core
## 155 0.6867533680 0.8055502874 2 TRUE Core
## 156 0.8577026713 0.4950936232 2 TRUE Core
## 157 -0.2189996056 1.1314297376 2 TRUE Core
## 158 1.5731753474 -0.3938428040 1 TRUE Core
## 159 -0.0869937037 0.9172648545 2 TRUE Core
## 160 1.4869671416 -0.3800248770 1 TRUE Core
## 161 -0.4067145425 0.9845884759 2 TRUE Core
## 162 -0.8658139812 0.4356358891 2 TRUE Core
## 163 0.9786229192 0.2818860150 2 TRUE Core
## 164 0.2911414585 0.0177467646 1 TRUE Core
## 165 1.9628732038 0.3893163943 1 TRUE Core
## 166 0.7808234676 -0.5715040511 1 TRUE Core
## 167 1.7543439058 -0.3052977808 1 TRUE Core
## 168 0.1921186348 -0.1467328688 1 TRUE Core
## 169 0.8826734377 0.6734255184 2 TRUE Core
## 170 1.8251388535 -0.2270995203 1 TRUE Core
## 171 -0.0433823544 0.2516312973 1 TRUE Core
## 172 -0.5607912503 0.8248000676 2 TRUE Core
## 173 2.0944068117 0.3910153489 1 TRUE Core
## 174 1.9110144881 0.1882530509 1 TRUE Core
## 175 0.2232489002 1.0357485205 2 TRUE Core
## 176 0.4802537664 -0.3300417554 1 TRUE Core
## 177 -0.6537788494 0.6712904655 2 TRUE Core
## 178 0.5760929750 -0.2984721960 1 TRUE Core
## 179 -0.9529252496 0.3159097992 2 TRUE Core
## 180 1.3778151650 -0.5445008016 1 TRUE Core
## 181 0.5229142591 -0.3553108641 1 TRUE Core
## 182 -0.7996718035 0.6011691039 2 TRUE Core
## 183 1.8669263119 0.0263027546 1 TRUE Core
## 184 0.2565066890 -0.1298425923 1 TRUE Core
## 185 -0.8365596736 0.5903724821 2 TRUE Core
## 186 -0.6395138944 0.9134906880 2 TRUE Core
## 187 2.0388775032 0.5304913648 1 TRUE Core
## 188 1.5338469439 -0.2829433666 1 TRUE Core
## 189 0.1877371429 -0.1663240141 1 TRUE Core
## 190 0.2720287882 -0.2020944746 1 TRUE Core
## 191 -0.3590720529 0.9954072551 2 TRUE Core
## 192 0.7597373691 0.7523740314 2 TRUE Core
## 193 0.6694232980 -0.2985814611 1 TRUE Core
## 194 0.7668077468 0.8723430099 2 TRUE Core
## 195 1.0333920520 0.0126220312 2 TRUE Core
## 196 0.1779218366 1.0235472599 2 TRUE Core
## 197 0.1572018698 0.2296247126 1 TRUE Core
## 198 -0.9102836936 0.3395791516 2 TRUE Core
## 199 -0.5883646898 0.7524609388 2 TRUE Core
## 200 1.1148050433 -0.4398278227 1 TRUE Core
## 201 2.0548939756 0.1427249938 1 TRUE Core
## 202 -0.1789097610 1.0320978164 2 TRUE Core
## 203 0.9513553202 0.4688139281 2 TRUE Core
## 204 -0.6498883322 0.7702430622 2 TRUE Core
## 205 0.2028552061 1.0159327815 2 TRUE Core
## 206 0.7252067529 0.7117569313 2 TRUE Core
## 207 0.8426281026 -0.5312595747 1 TRUE Core
## 208 0.5632472070 -0.3989796438 1 TRUE Core
## 209 0.1577184601 0.2712041637 1 TRUE Core
## 210 1.0153601790 0.1468731785 2 TRUE Core
## 211 1.6298859541 -0.3097615787 1 TRUE Core
## 212 0.8583861428 0.2978316697 2 TRUE Core
## 213 0.5705211021 0.9934405103 2 TRUE Core
## 214 0.7851267154 0.5721306805 2 TRUE Core
## 215 -0.4687330842 0.9663505480 2 TRUE Core
## 216 2.0004080975 0.0471603204 1 TRUE Core
## 217 0.1733051600 0.1297779437 1 TRUE Core
## 218 0.5040286690 0.8530385186 2 TRUE Core
## 219 0.1941224501 0.9654520917 2 TRUE Core
## 220 0.2687953190 -0.2327241220 1 TRUE Core
## 221 -0.9208395746 0.2917125574 2 TRUE Core
## 222 0.8230556489 0.6962781660 2 TRUE Core
## 223 -0.3387455051 0.9534180265 2 TRUE Core
## 224 0.0301349106 -0.0583565713 1 TRUE Core
## 225 1.8271411667 -0.0618734470 1 TRUE Core
## 226 2.1002573183 0.3474774827 1 TRUE Core
## 227 0.1256691329 1.1265403404 2 TRUE Core
## 228 1.0486419872 0.3558838777 2 TRUE Core
## 229 1.4488519834 -0.4610279219 1 TRUE Core
## 230 0.2959402787 1.0325672622 2 TRUE Core
## 231 2.1324240780 0.4328048372 1 TRUE Core
## 232 0.7309641078 0.5483875161 2 TRUE Core
## 233 1.5355781833 -0.4930042870 1 TRUE Core
## 234 1.0179916546 -0.5117773028 1 TRUE Core
## 235 1.7427245707 -0.2533464222 1 TRUE Core
## 236 0.5108372119 0.8401838456 2 TRUE Core
## 237 -0.0899908354 0.1854130985 1 TRUE Core
## 238 -0.9418938132 0.4838002711 2 TRUE Core
## 239 0.6798912058 -0.4280733732 1 TRUE Core
## 240 -0.2125266674 1.0239040772 2 TRUE Core
## 241 -0.7729440295 0.7450105709 2 TRUE Core
## 242 1.1914228752 -0.3933414357 1 TRUE Core
## 243 -0.1287891420 0.9763857869 2 TRUE Core
## 244 -1.0277759748 0.2221587619 2 TRUE Core
## 245 0.6561648678 -0.4160781320 1 TRUE Core
## 246 1.0084029074 0.2895588031 2 TRUE Core
## 247 -0.7410546822 0.4878116122 2 TRUE Core
## 248 1.9793433782 0.2464823144 1 TRUE Core
## 249 -1.0189105592 0.6358981985 2 TRUE Core
## 250 0.4976706958 -0.3501343432 1 TRUE Core
## 251 0.0054383713 0.5286965196 1 TRUE Core
## 252 0.4492165950 0.7763766402 2 TRUE Core
## 253 0.1125818828 0.0903407848 1 TRUE Core
## 254 0.0879071060 0.8893961707 2 TRUE Core
## 255 0.7990558072 -0.4740530709 1 TRUE Core
## 256 -0.1015253793 0.3595044524 1 TRUE Core
## 257 -0.2786595473 0.9107039775 2 TRUE Core
## 258 -0.3480405771 1.0232562774 2 TRUE Core
## 259 1.8677293146 0.1896434494 1 TRUE Core
## 260 0.3619094157 -0.1847432481 1 TRUE Core
## 261 0.9841823847 0.2134749583 2 TRUE Core
## 262 1.8957448812 0.2336733570 1 TRUE Core
## 263 0.9091697914 -0.1332462008 2 FALSE Border
## 264 1.1525792912 -0.4207398019 1 TRUE Core
## 265 -0.1836546620 0.3156313798 1 TRUE Core
## 266 1.2448154286 -0.3161472796 1 TRUE Core
## 267 0.4518672414 0.8346856229 2 TRUE Core
## 268 0.8568444111 0.6004280414 2 TRUE Core
## 269 0.7513840200 0.5319612601 2 TRUE Core
## 270 -0.0247619809 0.2578332248 1 TRUE Core
## 271 0.5964800997 -0.2806054269 1 TRUE Core
## 272 2.0204664090 0.3762215560 1 TRUE Core
## 273 -0.0091940556 0.8748446071 2 TRUE Core
## 274 1.4522424393 -0.4305571553 1 TRUE Core
## 275 1.9798509926 0.6487311401 1 TRUE Core
## 276 2.0171385904 0.3237638019 1 TRUE Core
## 277 -0.3746507856 1.0321048974 2 TRUE Core
## 278 0.2197409028 0.8624930007 2 TRUE Core
## 279 1.0468112300 -0.5530942945 1 TRUE Core
## 280 0.9239330401 0.7195048212 2 TRUE Core
## 281 1.9407648187 0.3871931682 1 TRUE Core
## 282 0.8971477185 -0.4258984635 1 TRUE Core
## 283 -0.3601867259 0.8492574694 2 TRUE Core
## 284 0.5844299005 -0.3489684241 1 TRUE Core
## 285 0.3887450135 -0.3437050635 1 TRUE Core
## 286 0.9064270610 0.2183647321 2 TRUE Core
## 287 0.7571038739 0.7204604838 2 TRUE Core
## 288 1.6166073103 -0.1758069230 1 TRUE Core
## 289 0.9673939730 0.2637445086 2 TRUE Core
## 290 0.7880226309 0.5219595116 2 TRUE Core
## 291 0.3338484240 -0.1800648918 1 TRUE Core
## 292 1.3848053192 -0.2499177646 1 TRUE Core
## 293 0.8387665750 -0.4521492298 1 TRUE Core
## 294 1.3619996956 -0.4663221303 1 TRUE Core
## 295 -0.2567104866 0.9352545819 2 TRUE Core
## 296 0.5590386726 0.9434784016 2 TRUE Core
## 297 0.9094803032 0.2322316168 2 TRUE Core
## 298 1.7421144908 -0.2805196949 1 TRUE Core
## 299 1.6939088326 -0.0527053148 1 TRUE Core
## 300 0.3297829299 0.9722924355 2 TRUE Core
## 301 -0.3334435608 0.9269535547 2 TRUE Core
## 302 1.0388247840 0.2804698957 2 TRUE Core
## 303 1.9470144393 0.2125944776 1 TRUE Core
## 304 0.7030122770 -0.5378631616 1 TRUE Core
## 305 -0.6428444023 0.6097464483 2 TRUE Core
## 306 2.0658932470 0.3727717297 1 TRUE Core
## 307 0.2242400706 -0.0521261855 1 TRUE Core
## 308 0.4946673098 -0.3451158209 1 TRUE Core
## 309 -1.0533489106 0.2196894938 2 TRUE Core
## 310 0.9012298985 0.1892165874 2 TRUE Core
## 311 0.0034988858 0.2338116520 1 TRUE Core
## 312 1.3779463727 -0.4554710546 1 TRUE Core
## 313 0.2952253030 -0.1974858661 1 TRUE Core
## 314 -0.9272073785 -0.0291409029 2 TRUE Core
## 315 0.0447976646 0.3940178095 1 TRUE Core
## 316 -0.1256093980 0.9447409621 2 TRUE Core
## 317 1.1992551694 -0.4730497509 1 TRUE Core
## 318 1.2387296779 -0.4384202685 1 TRUE Core
## 319 1.8792873667 0.0288012012 1 TRUE Core
## 320 1.2618710936 -0.4927068931 1 TRUE Core
## 321 1.0442482465 0.2899178928 2 TRUE Core
## 322 1.5428332348 -0.4108487780 1 TRUE Core
## 323 0.9522236780 0.4944490627 2 TRUE Core
## 324 0.4055445070 0.8828668757 2 TRUE Core
## 325 -1.0424257620 0.0210561955 2 TRUE Core
## 326 -0.1470897512 1.0000477274 2 TRUE Core
## 327 2.0290709794 0.2314863944 1 TRUE Core
## 328 -0.2906083687 0.9226363641 2 TRUE Core
## 329 1.4231909513 -0.3821358907 1 TRUE Core
## 330 -0.7989635827 0.7765436583 2 TRUE Core
## 331 0.1493208601 1.0460008046 2 TRUE Core
## 332 -0.2271571550 1.1135882717 2 TRUE Core
## 333 1.0402675503 -0.5262535020 1 TRUE Core
## 334 -0.0879260917 0.9720085281 2 TRUE Core
## 335 0.5392875757 0.7505231471 2 TRUE Core
## 336 1.5927433980 -0.3213723012 1 TRUE Core
## 337 0.4807492642 1.0512876693 2 TRUE Core
## 338 0.8271318739 0.5360032402 2 TRUE Core
## 339 0.0714053081 0.2361975758 1 TRUE Core
## 340 1.6434016605 -0.1773963594 1 TRUE Core
## 341 0.8458702401 -0.4325935211 1 TRUE Core
## 342 0.6021882764 0.8896548507 2 TRUE Core
## 343 1.7385162425 0.2569001889 1 TRUE Core
## 344 -0.9175642039 0.3549104608 2 TRUE Core
## 345 -0.0954736196 1.1005506822 2 TRUE Core
## 346 1.2998150559 -0.3742417935 1 TRUE Core
## 347 0.5819917920 0.9966988290 2 TRUE Core
## 348 2.1090824582 0.3502282663 1 TRUE Core
## 349 1.0390484338 -0.6276121628 1 TRUE Core
## 350 -1.0175051846 -0.0014682340 2 TRUE Core
## 351 1.0260279065 0.5088968532 2 TRUE Core
## 352 0.0648615141 1.0426049020 2 TRUE Core
## 353 0.7317829226 -0.3267764260 1 TRUE Core
## 354 1.2907302289 -0.4246606443 1 TRUE Core
## 355 0.8667222602 0.2716274634 2 TRUE Core
## 356 -0.3567619483 0.9484815309 2 TRUE Core
## 357 1.7649532408 -0.1563293126 1 TRUE Core
## 358 1.5850879355 -0.2231423693 1 TRUE Core
## 359 0.5067658923 -0.3670845502 1 TRUE Core
## 360 0.1711073688 -0.1661130980 1 TRUE Core
## 361 0.0208461659 0.9387880473 2 TRUE Core
## 362 0.5309708805 0.9700995940 2 TRUE Core
## 363 -0.9378309029 0.6251113399 2 TRUE Core
## 364 0.8067921043 0.6266394608 2 TRUE Core
## 365 -0.4019966505 0.8478045133 2 TRUE Core
## 366 0.0639807613 0.9323042975 2 TRUE Core
## 367 1.7081644215 -0.2812456943 1 TRUE Core
## 368 0.6817478040 0.8433618348 2 TRUE Core
## 369 0.1273443606 -0.1991729109 1 TRUE Core
## 370 0.5258137008 0.6155716663 2 TRUE Core
## 371 1.1577399596 -0.4499599967 1 TRUE Core
## 372 1.6894878419 -0.0064726944 1 TRUE Core
## 373 0.9392404117 0.2208853739 2 TRUE Core
## 374 1.8083266536 -0.1620681800 1 TRUE Core
## 375 1.2653207809 -0.5292848903 1 TRUE Core
## 376 1.0262210765 -0.5376602203 1 TRUE Core
## 377 0.0443935341 0.9191460099 2 TRUE Core
## 378 1.7114555366 -0.1857907183 1 TRUE Core
## 379 1.9448180617 0.1778080727 1 TRUE Core
## 380 0.8274704137 -0.4471903350 1 TRUE Core
## 381 0.7888701434 -0.3794203773 1 TRUE Core
## 382 -0.9464994631 0.3464815036 2 TRUE Core
## 383 0.2979687366 0.9891049810 2 TRUE Core
## 384 1.5978777906 -0.3302038000 1 TRUE Core
## 385 0.7928624686 -0.4584960114 1 TRUE Core
## 386 -0.8306316244 0.6822437033 2 TRUE Core
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## 1936 0.4056186418 -0.2055979009 1 TRUE Core
## 1937 0.9454251687 0.3866320134 2 TRUE Core
## 1938 -0.8305952187 0.4629869340 2 TRUE Core
## 1939 1.0046493829 0.0045995380 2 TRUE Core
## 1940 -0.3047278772 0.9789446693 2 TRUE Core
## 1941 1.8213925494 -0.0806770711 1 TRUE Core
## 1942 0.9958732743 -0.4648825560 1 TRUE Core
## 1943 0.1342105278 0.1346708942 1 TRUE Core
## 1944 1.1526986540 -0.4184208440 1 TRUE Core
## 1945 -0.8375087925 0.3929356574 2 TRUE Core
## 1946 0.3166168986 -0.1595988667 1 TRUE Core
## 1947 1.2766505147 -0.4195271649 1 TRUE Core
## 1948 1.9254594263 0.1082989907 1 TRUE Core
## 1949 -0.2051506129 1.0054707127 2 TRUE Core
## 1950 1.9361740398 0.3307682786 1 TRUE Core
## 1951 -0.6286009939 0.9224260270 2 TRUE Core
## 1952 -1.0148467061 0.2479157324 2 TRUE Core
## 1953 0.9508094773 0.5534911090 2 TRUE Core
## 1954 1.7407244951 -0.2372238208 1 TRUE Core
## 1955 -1.1149161781 -0.0345047214 2 TRUE Core
## 1956 -0.4767441768 0.8188371303 2 TRUE Core
## 1957 1.0295959939 -0.6776324445 1 TRUE Core
## 1958 1.5063543667 -0.2273851566 1 TRUE Core
## 1959 -0.0100718137 0.9876784755 2 TRUE Core
## 1960 0.0782516304 0.3758437481 1 TRUE Core
## 1961 0.0624214887 1.0023360244 2 TRUE Core
## 1962 1.2780217680 -0.2735321979 1 TRUE Core
## 1963 -1.0685271625 0.4893509223 2 TRUE Core
## 1964 -0.7112700557 0.7574340235 2 TRUE Core
## 1965 0.6494960715 0.7081750830 2 TRUE Core
## 1966 1.0547330319 0.3150243097 2 TRUE Core
## 1967 0.5755758547 -0.4400914459 1 TRUE Core
## 1968 0.0931170452 0.9556273066 2 TRUE Core
## 1969 0.0191368074 -0.0732860908 1 TRUE Core
## 1970 0.7050202844 0.6610652648 2 TRUE Core
## 1971 -0.9065637383 0.1769493237 2 TRUE Core
## 1972 0.1612538434 -0.1370925478 1 TRUE Core
## 1973 0.4802077652 0.9945551306 2 TRUE Core
## 1974 -0.8189000355 0.5539175893 2 TRUE Core
## 1975 0.8108456379 -0.5216880019 1 TRUE Core
## 1976 0.8803441696 -0.3354380414 1 TRUE Core
## 1977 0.4849490499 0.9131700933 2 TRUE Core
## 1978 -0.7542651735 0.6030448958 2 TRUE Core
## 1979 0.4824050959 -0.4924003364 1 TRUE Core
## 1980 1.7329889130 -0.4333837081 1 TRUE Core
## 1981 0.8350348859 0.3623023137 2 TRUE Core
## 1982 1.6591064607 -0.3299811624 1 TRUE Core
## 1983 -1.0189650983 0.4920911216 2 TRUE Core
## 1984 0.1323601431 0.1658455323 1 TRUE Core
## 1985 0.7374948147 -0.2559482947 1 TRUE Core
## 1986 1.1376141319 0.2152544934 2 TRUE Core
## 1987 1.0749056698 -0.4678326167 1 TRUE Core
## 1988 0.5480755606 0.7258881614 2 TRUE Core
## 1989 0.2536229073 -0.2455278786 1 TRUE Core
## 1990 0.1713986498 1.0801423958 2 TRUE Core
## 1991 0.7625152398 0.3696342447 2 TRUE Core
## 1992 1.5116545266 -0.4215740798 1 TRUE Core
## 1993 0.0678827412 0.3901658994 1 TRUE Core
## 1994 1.6761230229 -0.2826725239 1 TRUE Core
## 1995 -0.0530315919 0.1159517329 1 TRUE Core
## 1996 0.1391560125 0.1040336104 1 TRUE Core
## 1997 0.3867273394 -0.3322627421 1 TRUE Core
## 1998 -0.9303903588 0.5070835996 2 TRUE Core
## 1999 0.8461626537 -0.5991856123 1 TRUE Core
## 2000 0.1369722572 0.0976603079 1 TRUE Core
table(data$cluster)
##
## 0 1 2
## 1 1001 998
table(data$jenis)
##
## Border Core Noise
## 3 1996 1
# Plot hasil clustering
plot(M,
col = ifelse(data$cluster == 0, "red", "blue"),
pch = 19,
cex = 1,
xlab = "X",
ylab = "Y",
main = "Hasil Clustering DBSCAN")
legend("topright",
legend = c("Cluster", "Noise"),
col = c("blue", "red"),
pch = 19)
#plot berdasarkan jenis titik
plot(M,
col = ifelse(data$jenis == "Core", "blue",
ifelse(data$jenis == "Border", "green", "red")),
pch = 19,
cex = 1,
xlab = "X",
ylab = "Y",
main = "Jenis Titik pada DBSCAN")
legend("topright",
legend = c("Core Point", "Border Point", "Noise"),
col = c("blue", "green", "red"),
pch = 19)
#eksperimen parameter DBSCAN
# Kombinasi parameter
kombinasi <- expand.grid(
eps = c(0.10, 0.15, 0.20, 0.25, 0.30),
minPts = c(3, 5, 7, 10)
)
# Menyiapkan tabel hasil
hasil_eksperimen <- data.frame()
# Melakukan eksperimen
for (i in 1:nrow(kombinasi)) {
model <- dbscan(
M,
eps = kombinasi$eps[i],
minPts = kombinasi$minPts[i]
)
jumlah_cluster <- length(setdiff(unique(model$cluster), 0))
jumlah_noise <- sum(model$cluster == 0)
hasil_eksperimen <- rbind(
hasil_eksperimen,
data.frame(
eps = kombinasi$eps[i],
minPts = kombinasi$minPts[i],
jumlah_cluster = jumlah_cluster,
jumlah_noise = jumlah_noise
)
)
}
# Menampilkan hasil eksperimen
print(hasil_eksperimen)
## eps minPts jumlah_cluster jumlah_noise
## 1 0.10 3 2 4
## 2 0.15 3 2 1
## 3 0.20 3 1 0
## 4 0.25 3 1 0
## 5 0.30 3 1 0
## 6 0.10 5 2 5
## 7 0.15 5 2 1
## 8 0.20 5 1 0
## 9 0.25 5 1 0
## 10 0.30 5 1 0
## 11 0.10 7 2 7
## 12 0.15 7 2 1
## 13 0.20 7 1 0
## 14 0.25 7 1 0
## 15 0.30 7 1 0
## 16 0.10 10 2 10
## 17 0.15 10 2 1
## 18 0.20 10 1 0
## 19 0.25 10 1 0
## 20 0.30 10 1 0
#membandingkan hasil eksperimen
hasil_eksperimen[
order(hasil_eksperimen$eps, hasil_eksperimen$minPts),
]
## eps minPts jumlah_cluster jumlah_noise
## 1 0.10 3 2 4
## 6 0.10 5 2 5
## 11 0.10 7 2 7
## 16 0.10 10 2 10
## 2 0.15 3 2 1
## 7 0.15 5 2 1
## 12 0.15 7 2 1
## 17 0.15 10 2 1
## 3 0.20 3 1 0
## 8 0.20 5 1 0
## 13 0.20 7 1 0
## 18 0.20 10 1 0
## 4 0.25 3 1 0
## 9 0.25 5 1 0
## 14 0.25 7 1 0
## 19 0.25 10 1 0
## 5 0.30 3 1 0
## 10 0.30 5 1 0
## 15 0.30 7 1 0
## 20 0.30 10 1 0