library(readxl)
AKU <- read_excel("C:/Users/viora/OneDrive/SEMESTER 4/STATISTIKA MULTIVARIAT/Data Analisis AKU.xlsx")
head(AKU)
## # A tibble: 6 × 9
## X1 X2 X3 X4 X5 X6 X7 X8 X9
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2893654 1.32e10 0.73 7097 333291 195720 16.1 77.8 5
## 2 384222592 2.89e17 6.42 6827541 30972246 45126932 11.5 70.6 6
## 3 9086139 4.02e16 0.22 14611 411040 409776 3.6 77.4 5
## 4 9535079 7.52e10 0.16 22821 949294 517708 5.2 70.8 4
## 5 10816860 3.09e 9 24.2 69246 583308 2046794 6.9 56.7 6
## 6 11231213 5.32e16 2.49 6538 1210112 773568 8.5 80.6 6
#uji multikolinearitas
VIF <- function(x){
VIF<-diag(solve(cor(x)))
result<-ifelse(VIF>10,"multicolinearity","non multicolinearity")
data1 <- data.frame(VIF,result)
return(data1)
}
VIF(AKU)
## VIF result
## X1 292.855493 multicolinearity
## X2 4.703383 non multicolinearity
## X3 2.299950 non multicolinearity
## X4 41.842203 multicolinearity
## X5 444.394159 multicolinearity
## X6 499.131747 multicolinearity
## X7 1.059021 non multicolinearity
## X8 2.263531 non multicolinearity
## X9 1.307734 non multicolinearity
# Standardisasi data dan PCA langsung
pca_result <- prcomp(AKU, center = FALSE, scale. = TRUE)
# Menampilkan hasil PCA
print(pca_result)
## Standard deviations (1, .., p=9):
## [1] 2.34847284 1.47091253 0.78847414 0.60163477 0.44163255 0.36032788 0.09844833
## [8] 0.04359136 0.03111256
##
## Rotation (n x k) = (9 x 9):
## PC1 PC2 PC3 PC4 PC5 PC6
## X1 -0.3834183 -0.2822707 0.01573283 -0.05028958 0.07851595 0.3199478
## X2 -0.3211657 -0.2326124 0.43719004 0.67726890 -0.26398369 -0.3464694
## X3 -0.2350756 0.3743414 -0.68822941 0.47686456 -0.22589972 0.1997075
## X4 -0.3580857 -0.1939908 -0.38519549 -0.38519225 -0.16775346 -0.6790714
## X5 -0.3798273 -0.2857451 0.04145964 -0.03504451 0.10074845 0.4252346
## X6 -0.3854999 -0.2700739 -0.10596446 -0.17093228 0.04231230 0.1697507
## X7 -0.2509890 0.4494130 0.35040280 -0.36191039 -0.67091818 0.1764013
## X8 -0.3182623 0.4078914 0.21563780 -0.03195597 0.48159544 -0.1439430
## X9 -0.3304419 0.4068331 0.06597652 0.02363546 0.38854857 -0.1228601
## PC7 PC8 PC9
## X1 0.030061834 0.799525544 0.1478545094
## X2 0.005078115 -0.044192320 0.0347647657
## X3 -0.112017776 0.009251746 0.0010393027
## X4 -0.038411922 0.070550385 -0.2041117060
## X5 -0.041069306 -0.338625486 -0.6810325462
## X6 0.013177818 -0.488106741 0.6848183581
## X7 0.002854420 0.003791083 0.0002091623
## X8 -0.656297799 0.013578508 0.0353257656
## X9 0.743270980 -0.025076537 -0.0351897776
summary(pca_result)
## Importance of components:
## PC1 PC2 PC3 PC4 PC5 PC6 PC7
## Standard deviation 2.3485 1.4709 0.78847 0.60163 0.44163 0.36033 0.09845
## Proportion of Variance 0.6128 0.2404 0.06908 0.04022 0.02167 0.01443 0.00108
## Cumulative Proportion 0.6128 0.8532 0.92229 0.96251 0.98418 0.99860 0.99968
## PC8 PC9
## Standard deviation 0.04359 0.03111
## Proportion of Variance 0.00021 0.00011
## Cumulative Proportion 0.99989 1.00000
#standarisasi karena skalanya berbeda
data_scaled<-scale(AKU)
data_scaled
## X1 X2 X3 X4 X5 X6
## [1,] -0.47765937 -0.40374534 -0.76259274 -0.48585592 -0.46632897 -0.48671462
## [2,] -0.19714366 -0.15843642 0.46105678 0.02361702 -0.18214816 -0.16356807
## [3,] -0.47310402 -0.36962341 -0.87226959 -0.48529464 -0.46560783 -0.48517513
## [4,] -0.47277377 -0.40374529 -0.88517274 -0.48468137 -0.46061545 -0.48439888
## [5,] -0.47183085 -0.40374535 4.29544535 -0.48121352 -0.46401002 -0.47340165
## [6,] -0.47152604 -0.35860444 -0.38410009 -0.48589768 -0.45819632 -0.48255872
## [7,] -0.47199150 -0.40374535 1.41158945 -0.48114017 -0.46110268 -0.47277928
## [8,] -0.46684894 -0.40374535 0.55783047 -0.41492122 -0.46161167 -0.46946595
## [9,] -0.47447390 -0.40374531 -0.89807590 -0.48567538 -0.46460729 -0.48626066
## [10,] -0.47697973 -0.40374534 -0.89162432 -0.48626146 -0.46666130 -0.48696416
## [11,] -0.47281208 -0.40374529 -0.91312959 -0.48473299 -0.46340498 -0.48546995
## [12,] -0.47952930 -0.40374535 0.55783047 -0.48635640 -0.46907623 -0.48774842
## [13,] -0.47922526 -0.40374535 0.42449783 -0.48556684 -0.46873182 -0.48739105
## [14,] -0.40365348 -0.27965329 -0.69592642 -0.47009071 -0.39633885 -0.45128143
## [15,] -0.47376424 -0.34409311 -0.65291589 -0.48626124 -0.46370562 -0.48464212
## [16,] -0.46672135 -0.38178168 -0.04861798 -0.47882498 -0.45498471 -0.47755644
## [17,] -0.46348867 -0.40374533 2.30835896 -0.42073779 -0.45626478 -0.46527408
## [18,] -0.46303559 -0.40374533 1.81803894 -0.47195061 -0.45086929 -0.45832729
## [19,] -0.44463140 -0.37162188 -0.58194852 -0.46329185 -0.42464023 -0.45545142
## [20,] -0.47940998 -0.40374535 1.02019364 -0.48630830 -0.46886542 -0.48764022
## [21,] -0.47628820 -0.40374531 -0.02066113 -0.48521793 -0.46515154 -0.48470078
## [22,] -0.47893936 -0.40374534 -0.89162432 -0.48627139 -0.46887645 -0.48774014
## [23,] -0.42021514 -0.07443588 -0.83140958 -0.48606620 -0.40262929 -0.46753370
## [24,] -0.47563653 -0.37436355 -0.71313063 -0.48583322 -0.46428380 -0.48476009
## [25,] -0.47213313 -0.40374530 0.58148626 -0.47302118 -0.46078450 -0.47900326
## [26,] 1.00666033 -0.29556239 -0.75829169 -0.01565414 0.82684129 0.71713514
## [27,] 1.78520775 0.46825481 -0.18840219 1.07246948 2.06168804 2.07091080
## [28,] 1.18571796 1.43202034 -0.76044221 -0.00169624 0.96091970 0.80923948
## [29,] -0.17892833 -0.07503265 -0.75614116 -0.40345247 -0.13168062 -0.33649094
## [30,] 0.18520947 1.58595865 -0.65506642 -0.38008861 0.25537115 -0.13319058
## [31,] -0.46808942 -0.39506186 -0.62926010 -0.48166328 -0.45200466 -0.47325240
## [32,] -0.23069225 0.73796518 -0.44001378 -0.47226285 -0.20920219 -0.35759894
## [33,] -0.44559545 -0.28648433 -0.42065904 -0.48424656 -0.43891967 -0.46682934
## [34,] -0.10583611 1.17297206 -0.57764747 -0.45576820 -0.07256907 -0.28238697
## [35,] -0.13081016 -0.33496726 1.46105156 0.76380821 -0.19619769 0.02694644
## [36,] -0.47577039 -0.38061615 -0.84861380 -0.48625750 -0.46444023 -0.48559234
## [37,] -0.46008309 -0.40374532 -0.34969167 -0.45551236 -0.44840566 -0.45851157
## [38,] -0.47075782 -0.40374535 2.01373684 -0.45526451 -0.46278205 -0.47568270
## [39,] -0.46800660 -0.40374531 1.08255891 -0.46714948 -0.45860896 -0.47073603
## [40,] 0.38869087 3.84675672 -0.60990537 -0.31385621 0.37315067 0.05763350
## [41,] -0.47446084 -0.37902312 -0.80560327 -0.48624316 -0.46556210 -0.48579080
## [42,] -0.47393120 -0.40374534 -0.56689484 -0.48235566 -0.46367126 -0.47985111
## [43,] 0.03641156 -0.34942900 1.24169786 1.20089431 -0.10907597 0.36771044
## [44,] -0.47667015 -0.40374531 -0.87872116 -0.48618616 -0.46598518 -0.48696563
## [45,] -0.47252999 -0.39192070 -0.54754010 -0.48519500 -0.46146400 -0.48529564
## [46,] 2.81630220 1.87067746 -0.37979904 0.68106077 2.99609720 2.52775213
## [47,] 4.01081595 2.07161899 -0.03786534 3.89571329 3.96607425 4.14652307
## [48,] 0.71472573 -0.20214339 0.59653994 2.72826647 0.50055683 1.13064859
## [49,] -0.05754486 -0.29516087 -0.45721799 0.75345231 -0.10505813 -0.01060453
## [50,] -0.29260432 -0.32815251 -0.44431483 -0.33637666 -0.25992296 -0.27352334
## [51,] 0.29248257 -0.31169561 1.03739786 1.48842810 0.13619467 0.65313092
## [52,] -0.42230348 -0.36763972 -0.65076537 -0.48304385 -0.41567511 -0.43460580
## [53,] -0.47374434 -0.37753416 -0.62280852 -0.48457284 -0.46229949 -0.48192488
## [54,] -0.46706961 -0.38494950 -0.91097906 -0.48600435 -0.45400884 -0.48005076
## [55,] -0.47549527 -0.40374535 -0.91312959 -0.48577742 -0.46338666 -0.48499629
## [56,] -0.03926056 0.08469341 0.11052098 -0.22642992 0.10442229 -0.03471025
## [57,] -0.47486720 -0.40374535 0.56858310 -0.48365966 -0.46384827 -0.48185876
## [58,] -0.47655380 -0.40374535 0.37933678 -0.45333559 -0.46735326 -0.48320306
## [59,] -0.01907567 0.12535795 0.10621993 -0.21499539 0.12550599 -0.01817828
## [60,] 0.20578293 -0.32270389 1.14277365 1.34462864 0.04750880 0.56054788
## [61,] -0.02272702 -0.36925839 1.28255786 0.96470100 -0.14134132 0.27091299
## [62,] 1.64267744 0.09620525 -0.25291798 1.78268305 1.75588674 1.89245574
## [63,] 3.99295627 2.00085524 -0.04001587 3.89343321 3.95643967 4.13758424
## [64,] -0.47823644 -0.40374535 0.96212943 -0.48146488 -0.46820677 -0.48548962
## [65,] 1.16491595 1.26388004 -0.59700221 -0.08402178 1.05319331 0.65476472
## [66,] -0.47763090 -0.40374531 -0.80345274 -0.48634415 -0.46684784 -0.48734468
## [67,] -0.47832134 -0.40374533 -0.75614116 -0.48613246 -0.46829262 -0.48729787
## [68,] -0.17347175 -0.37371915 0.34492836 -0.30274482 -0.14206040 -0.14392718
## [69,] -0.38755087 -0.29354373 -0.74323800 -0.46098413 -0.34890532 -0.38292180
## [70,] 3.53589526 1.96633075 -0.30022956 2.44234616 3.62836066 3.37854884
## [71,] -0.46721909 -0.40374534 3.39437479 -0.40947171 -0.46050645 -0.47243200
## [72,] -0.47947364 -0.40374535 -0.81635590 -0.48632323 -0.46913990 -0.48794912
## [73,] -0.44047823 -0.40374530 -0.87657064 -0.46515108 -0.43982081 -0.45088713
## [74,] -0.21771154 -0.27062615 0.49116415 -0.31568638 -0.19289907 -0.18520785
## [75,] -0.47764745 -0.40374535 -0.90882853 -0.48561585 -0.46677134 -0.48640127
## [76,] -0.45976701 -0.40374534 0.45890625 -0.43577277 -0.46215267 -0.44734639
## [77,] -0.47686786 -0.40374535 -0.16904745 -0.47513401 -0.46776033 -0.48386278
## [78,] -0.47886045 -0.40374534 -0.70882958 -0.48612170 -0.46818669 -0.48736387
## [79,] -0.46572746 -0.40374535 -0.09162850 -0.39425873 -0.46464289 -0.47174585
## [80,] -0.45906195 -0.40374534 1.27825681 -0.47340625 -0.44007423 -0.45646452
## [81,] 0.45812257 3.74732585 -0.62065800 -0.27879024 0.52876315 0.15423400
## [82,] -0.47667187 -0.40374529 -0.91958117 -0.48595931 -0.46579279 -0.48644430
## [83,] -0.45908529 -0.36609915 1.55567472 -0.44816918 -0.45067216 -0.46208969
## [84,] -0.34366452 -0.38300171 -0.42926115 -0.06719690 -0.36473516 -0.34836989
## [85,] -0.45700335 -0.38668082 -0.01636008 -0.47430778 -0.44464779 -0.46298169
## [86,] 0.12809854 -0.27782986 0.97503259 1.95141249 -0.03750690 0.49252303
## [87,] -0.37399052 -0.22948369 -0.83786116 -0.46995169 -0.38537518 -0.44694409
## [88,] 0.78633762 -0.18433785 -0.22496114 0.35937435 0.95145979 0.88640603
## [89,] -0.45706706 -0.33975306 -0.71313063 -0.47736389 -0.43770447 -0.46124504
## [90,] -0.47529503 -0.40374533 0.38363783 -0.48334070 -0.46362277 -0.48253373
## [91,] -0.47454258 -0.40374532 -0.82280748 -0.48608913 -0.46433604 -0.48607429
## [92,] 0.23691863 -0.25355151 0.83954943 2.06335165 0.05119459 0.64984100
## [93,] 0.23698587 -0.25343097 0.83954943 2.06338511 0.05125818 0.64990429
## [94,] -0.45221721 -0.35953185 1.22234313 -0.44307172 -0.44306628 -0.45431978
## [95,] -0.47827118 -0.40374531 -0.75184011 -0.48620275 -0.46807373 -0.48731927
## [96,] -0.47265531 -0.35503433 -0.91958117 -0.48625257 -0.46175258 -0.48267670
## [97,] 0.98821668 0.67602144 -0.75829169 -0.01980660 0.80470767 0.70391827
## [98,] -0.14784801 -0.02390466 -0.75399063 -0.39862280 -0.10361169 -0.31973861
## [99,] -0.03094549 0.10727907 0.11912308 -0.22240706 0.11463612 -0.02618804
## [100,] -0.22087082 -0.27171868 0.50406731 -0.31814013 -0.19947725 -0.18839015
## [101,] -0.47889637 -0.40374535 2.89760319 -0.48609705 -0.46831715 -0.48635411
## [102,] 0.78633762 -0.18433785 -0.22496114 0.35937435 0.95145979 0.88640603
## [103,] 0.23698587 -0.25343097 0.83954943 2.06338511 0.05125818 0.64990429
## [104,] -0.44641787 -0.39241238 -0.90667801 -0.48216831 -0.44425082 -0.47600346
## [105,] 1.41342980 1.46587420 -0.37119693 0.17327705 1.40305363 0.99797108
## [106,] -0.47662874 -0.40374534 -0.87657064 -0.48393230 -0.46284211 -0.48493995
## [107,] 4.86143517 6.24963407 -0.10023061 4.06596299 4.79901034 4.68334022
## X7 X8 X9
## [1,] 1.39700419 0.88946023 -0.7859423
## [2,] 0.58951227 -0.04968849 0.4882369
## [3,] -0.80684930 0.82995494 -0.7859423
## [4,] -0.52475605 -0.02511022 -2.0601216
## [5,] -0.22503198 -1.84519596 0.4882369
## [6,] 0.05706127 1.24649197 0.4882369
## [7,] -1.26525083 -1.48040265 0.4882369
## [8,] -0.89500344 -1.59941324 0.4882369
## [9,] 0.60361693 0.57641066 -2.0601216
## [10,] 3.47744189 0.70835717 -0.7859423
## [11,] -0.40134026 0.26206749 -2.0601216
## [12,] 0.58598611 -0.11307456 0.4882369
## [13,] -0.94789592 -0.19198375 1.7624162
## [14,] 0.15579390 0.72517388 -0.7859423
## [15,] -0.64817185 1.53884406 0.4882369
## [16,] -0.31318612 1.36420896 0.4882369
## [17,] -0.73632599 -2.50880931 0.4882369
## [18,] -0.68343350 -2.00042715 0.4882369
## [19,] 0.33915452 0.39272041 -0.7859423
## [20,] 0.18047706 0.28405858 0.4882369
## [21,] 0.02179961 1.09255437 0.4882369
## [22,] 1.30885005 1.18698668 0.4882369
## [23,] -0.56001771 1.27883181 -2.0601216
## [24,] -0.27792446 1.24131760 1.7624162
## [25,] 1.20306508 0.32933434 0.4882369
## [26,] -0.63406719 0.39272041 0.4882369
## [27,] -0.44365424 -0.24760826 0.4882369
## [28,] -0.64464568 0.51431818 0.4882369
## [29,] -0.09809002 0.12106582 -2.0601216
## [30,] 0.14697849 0.76786246 -0.7859423
## [31,] -0.63054102 0.63591595 0.4882369
## [32,] 0.59127535 1.38361286 0.4882369
## [33,] 2.91325539 1.56859670 0.4882369
## [34,] 0.35854843 1.25684072 0.4882369
## [35,] -0.05048678 -1.19451854 0.4882369
## [36,] 0.07469210 1.31634601 0.4882369
## [37,] -1.01841924 -1.24755586 0.4882369
## [38,] -1.12420420 -1.58130293 0.4882369
## [39,] -0.93026510 0.09907474 0.4882369
## [40,] -0.14216709 1.24519838 0.4882369
## [41,] -0.87737261 1.68502010 0.4882369
## [42,] -0.75395682 0.28276498 0.4882369
## [43,] -0.27792446 -1.31482271 0.4882369
## [44,] 1.50278916 0.82478057 -2.0601216
## [45,] -0.06635453 0.63591595 -2.0601216
## [46,] -0.45246966 0.14176332 0.4882369
## [47,] -0.44189116 -0.15576314 0.4882369
## [48,] -0.40662951 -0.97590128 0.4882369
## [49,] -0.51594064 -0.98754362 0.4882369
## [50,] -0.34844777 -0.26701216 0.4882369
## [51,] -0.35021086 -0.96943331 0.4882369
## [52,] 0.81518687 0.57382347 0.4882369
## [53,] -0.36607860 1.44829253 0.4882369
## [54,] -0.71869516 0.08613880 -2.0601216
## [55,] -0.01346204 -0.07167958 -2.0601216
## [56,] -0.28850296 0.48715272 0.4882369
## [57,] -1.19472751 -0.62533750 -0.7859423
## [58,] -0.77158764 -1.30964834 0.4882369
## [59,] -0.28145063 0.51561177 0.4882369
## [60,] -0.36078935 -1.00436033 0.4882369
## [61,] -0.38723560 -1.25273024 0.4882369
## [62,] -0.51594064 -0.47916146 0.4882369
## [63,] -0.44718041 -0.16481829 0.4882369
## [64,] 3.17771781 -2.74941766 1.7624162
## [65,] -0.54238688 0.53889645 0.4882369
## [66,] 0.55072445 0.39013322 -2.0601216
## [67,] 0.32152369 0.41859228 0.4882369
## [68,] 0.54367212 0.24525078 0.4882369
## [69,] -0.57764854 0.74587138 0.4882369
## [70,] -0.45423274 -0.04063334 0.4882369
## [71,] -0.01346204 -1.67702883 0.4882369
## [72,] -0.40134026 1.39654879 0.4882369
## [73,] -0.85974178 -0.65897092 -0.7859423
## [74,] 0.82929153 0.17022237 0.4882369
## [75,] -0.59527937 -0.19327734 -0.7859423
## [76,] 2.54300801 -2.05993244 1.7624162
## [77,] 4.02399755 -1.02635141 0.4882369
## [78,] -0.08398536 0.41859228 0.4882369
## [79,] -0.54238688 -1.22815197 0.4882369
## [80,] -0.96552675 -0.17516704 -0.7859423
## [81,] -0.14745634 1.18569309 0.4882369
## [82,] -0.17213949 0.79373433 -2.0601216
## [83,] 0.49606888 -0.58264892 0.4882369
## [84,] -0.52475605 -0.61757594 -0.7859423
## [85,] -0.70106433 0.46257445 0.4882369
## [86,] -0.06988069 -1.62916588 0.4882369
## [87,] -0.54238688 -0.07556035 -2.0601216
## [88,] -0.75395682 -0.36661884 -0.7859423
## [89,] -0.45423274 0.43799618 0.4882369
## [90,] -0.34844777 0.23231485 0.4882369
## [91,] 2.47248470 0.59193378 -2.0601216
## [92,] -0.03638212 -1.60329402 0.4882369
## [93,] -0.03638212 -1.60329402 0.4882369
## [94,] 0.44846565 -0.40283945 0.4882369
## [95,] 0.23336955 1.23743682 0.4882369
## [96,] -0.03109287 1.42371425 0.4882369
## [97,] -0.63230410 0.39789478 0.4882369
## [98,] -0.06106528 0.18703908 -2.0601216
## [99,] -0.27792446 0.50138225 0.4882369
## [100,] 0.80813454 0.16892877 0.4882369
## [101,] -0.61291019 -0.34850854 0.4882369
## [102,] -0.75395682 -0.36661884 -0.7859423
## [103,] -0.03638212 -1.60329402 0.4882369
## [104,] -0.08398536 0.03051429 -2.0601216
## [105,] -0.40134026 0.45093211 0.4882369
## [106,] 3.17771781 0.25171874 -2.0601216
## [107,] -0.39605101 0.06414772 0.4882369
## attr(,"scaled:center")
## X1 X2 X3 X4 X5 X6
## 6.522168e+08 4.756138e+17 4.276075e+00 6.511374e+06 5.061055e+07 6.786990e+07
## X7 X8 X9
## 8.176355e+00 7.095411e+01 5.616822e+00
## attr(,"scaled:scale")
## X1 X2 X3 X4 X5 X6
## 1.359385e+09 1.178004e+18 4.650024e+00 1.338725e+07 1.078150e+08 1.390428e+08
## X7 X8 X9
## 5.671883e+00 7.730405e+00 7.848189e-01
head(data_scaled)
## X1 X2 X3 X4 X5 X6
## [1,] -0.4776594 -0.4037453 -0.7625927 -0.48585592 -0.4663290 -0.4867146
## [2,] -0.1971437 -0.1584364 0.4610568 0.02361702 -0.1821482 -0.1635681
## [3,] -0.4731040 -0.3696234 -0.8722696 -0.48529464 -0.4656078 -0.4851751
## [4,] -0.4727738 -0.4037453 -0.8851727 -0.48468137 -0.4606154 -0.4843989
## [5,] -0.4718309 -0.4037454 4.2954453 -0.48121352 -0.4640100 -0.4734016
## [6,] -0.4715260 -0.3586044 -0.3841001 -0.48589768 -0.4581963 -0.4825587
## X7 X8 X9
## [1,] 1.39700419 0.88946023 -0.7859423
## [2,] 0.58951227 -0.04968849 0.4882369
## [3,] -0.80684930 0.82995494 -0.7859423
## [4,] -0.52475605 -0.02511022 -2.0601216
## [5,] -0.22503198 -1.84519596 0.4882369
## [6,] 0.05706127 1.24649197 0.4882369
#membuat matriks korelasi
cor_matriks<-cor(data_scaled)
cor_matriks
## X1 X2 X3 X4 X5 X6
## X1 1.00000000 0.7564621 -0.055578491 0.8125076 0.99678908 0.986774745
## X2 0.75646207 1.0000000 -0.138992339 0.4887608 0.75720164 0.688467634
## X3 -0.05557849 -0.1389923 1.000000000 0.1475211 -0.06866166 0.000931779
## X4 0.81250758 0.4887608 0.147521066 1.0000000 0.78396282 0.885149208
## X5 0.99678908 0.7572016 -0.068661663 0.7839628 1.00000000 0.980488400
## X6 0.98677474 0.6884676 0.000931779 0.8851492 0.98048840 1.000000000
## X7 -0.18358008 -0.1097745 -0.113335238 -0.1592406 -0.18078785 -0.183577614
## X8 -0.03975786 0.1720094 -0.677928218 -0.3009495 -0.01873304 -0.112803364
## X9 0.17298059 0.1374573 0.400525688 0.2079581 0.16221551 0.190103498
## X7 X8 X9
## X1 -0.18358008 -0.03975786 0.17298059
## X2 -0.10977450 0.17200936 0.13745731
## X3 -0.11333524 -0.67792822 0.40052569
## X4 -0.15924059 -0.30094946 0.20795813
## X5 -0.18078785 -0.01873304 0.16221551
## X6 -0.18357761 -0.11280336 0.19010350
## X7 1.00000000 0.06351039 -0.05645761
## X8 0.06351039 1.00000000 -0.20177527
## X9 -0.05645761 -0.20177527 1.00000000
#mencari nilai eigen dari matriks korelasi
eig<-eigen(cor_matriks)
print(eig$values)
## [1] 4.382661364 1.972135682 0.953909181 0.853118059 0.427133284 0.245548594
## [7] 0.161981031 0.002329400 0.001183405
#mencari vektor eigen
print(eig$vectors)
## [,1] [,2] [,3] [,4] [,5] [,6]
## [1,] -0.47001341 0.07171002 -0.025086994 -0.04038552 -0.017370457 -0.04549339
## [2,] -0.37049495 0.20008676 -0.056831158 0.22218189 0.733242925 0.30014806
## [3,] -0.01467620 -0.64515493 -0.009543325 0.01067138 0.438404116 -0.62440517
## [4,] -0.41576144 -0.13719359 -0.052127728 -0.23080868 -0.392050534 -0.16491107
## [5,] -0.46601964 0.08663249 -0.022759601 -0.03229938 0.004499412 -0.05498588
## [6,] -0.47098808 0.01457716 -0.032310989 -0.09722929 -0.150849977 -0.11163576
## [7,] 0.11108716 0.10358443 -0.972570646 -0.15499549 0.041635000 -0.06654913
## [8,] 0.05416344 0.60470274 0.042547665 0.42596316 -0.047974195 -0.65894192
## [9,] -0.12029057 -0.36832482 -0.209920277 0.82441051 -0.298898532 0.19142831
## [,7] [,8] [,9]
## [1,] 0.32894936 0.800692514 -0.1414113129
## [2,] -0.37257177 -0.046546428 -0.0373345646
## [3,] 0.03430772 0.009690556 0.0019664073
## [4,] -0.72385458 0.070849724 0.2060242158
## [5,] 0.43347593 -0.344444967 0.6813015858
## [6,] 0.16545660 -0.482615469 -0.6869849836
## [7,] 0.02901449 0.002903828 0.0003375502
## [8,] -0.10770100 0.006333774 0.0006338215
## [9,] 0.01102299 -0.001661936 0.0061961605
vektor_eig<-eig$vector
#proporsi total varians
proporsi <- eig$values / sum(eig$values)
proporsi
## [1] 0.4869623737 0.2191261869 0.1059899090 0.0947908955 0.0474592538
## [6] 0.0272831771 0.0179978924 0.0002588222 0.0001314895
#proporsi kumulatif
prop_kumulatif<-cumsum(proporsi)
prop_kumulatif
## [1] 0.4869624 0.7060886 0.8120785 0.9068694 0.9543286 0.9816118 0.9996097
## [8] 0.9998685 1.0000000
#dengan 80% proporsi keragaman maka ada 3 nilai proporsi yang diambil
#menentukan KOMPONEN UTAMA
pca_result<-prcomp(data_scaled, center = TRUE , scale. = TRUE)
pca_result
## Standard deviations (1, .., p=9):
## [1] 2.09348068 1.40432748 0.97668274 0.92364390 0.65355435 0.49552860 0.40246867
## [8] 0.04826386 0.03440066
##
## Rotation (n x k) = (9 x 9):
## PC1 PC2 PC3 PC4 PC5 PC6
## X1 0.47001341 0.07171002 -0.025086994 -0.04038552 0.017370457 0.04549339
## X2 0.37049495 0.20008676 -0.056831158 0.22218189 -0.733242925 -0.30014806
## X3 0.01467620 -0.64515493 -0.009543325 0.01067138 -0.438404116 0.62440517
## X4 0.41576144 -0.13719359 -0.052127728 -0.23080868 0.392050534 0.16491107
## X5 0.46601964 0.08663249 -0.022759601 -0.03229938 -0.004499412 0.05498588
## X6 0.47098808 0.01457716 -0.032310989 -0.09722929 0.150849977 0.11163576
## X7 -0.11108716 0.10358443 -0.972570646 -0.15499549 -0.041635000 0.06654913
## X8 -0.05416344 0.60470274 0.042547665 0.42596316 0.047974195 0.65894192
## X9 0.12029057 -0.36832482 -0.209920277 0.82441051 0.298898532 -0.19142831
## PC7 PC8 PC9
## X1 0.32894936 -0.800692514 0.1414113129
## X2 -0.37257177 0.046546428 0.0373345646
## X3 0.03430772 -0.009690556 -0.0019664073
## X4 -0.72385458 -0.070849724 -0.2060242158
## X5 0.43347593 0.344444967 -0.6813015858
## X6 0.16545660 0.482615469 0.6869849836
## X7 0.02901449 -0.002903828 -0.0003375502
## X8 -0.10770100 -0.006333774 -0.0006338215
## X9 0.01102299 0.001661936 -0.0061961605
#scree plot
screeplot(pca_result,type = "lines", main = "scree plot")
#menghitung skor komponen utama
y<-data_scaled%*%vektor_eig
y
## [,1] [,2] [,3] [,4] [,5]
## [1,] 1.33174618 1.368164571 -1.061983296 -0.38961866 -0.10985715
## [2,] 0.30076333 -0.513507915 -0.660197872 0.28398646 -0.01502829
## [3,] 1.06923541 1.181817127 1.077785906 -0.06745400 -0.22235115
## [4,] 1.21725982 1.165169765 1.036408697 -1.53396078 0.18024794
## [5,] 0.76391533 -4.185861259 0.082590517 -0.20132636 1.78649758
## [6,] 1.01807001 0.742009953 -0.017727893 1.03375930 -0.36527280
## [7,] 0.70883989 -2.212247019 1.137233439 0.08435180 0.46128634
## [8,] 0.72478185 -1.703766204 0.776549449 -0.04863709 0.08156697
## [9,] 1.37932689 1.653758988 -0.035051824 -1.45215742 0.19339559
## [10,] 1.55506219 1.557469321 -3.091810335 -0.79049614 -0.07093449
## [11,] 1.24877847 1.369394420 0.928965407 -1.43085318 0.15952277
## [12,] 1.01755537 -0.643587710 -0.595774789 0.37396038 0.10287285
## [13,] 0.69077187 -1.233533730 0.626404649 1.62687631 -0.39687580
## [14,] 1.04736775 1.131793189 0.125086661 -0.25126747 -0.04593348
## [15,] 0.95888311 1.021457969 0.682608542 1.26850880 -0.51539926
## [16,] 0.97792817 0.553491836 0.344764062 1.13730299 -0.25984970
## [17,] 0.66383459 -3.365042786 0.566787643 -0.44129351 0.90085369
## [18,] 0.71973513 -2.728184237 0.543966708 -0.22721957 0.68275482
## [19,] 1.11371756 0.851431974 -0.061798183 -0.43911268 -0.04126900
## [20,] 0.98700760 -0.743718722 -0.188917787 0.61087734 0.26960295
## [21,] 1.02341148 0.400695851 0.009425409 0.96797021 -0.23301392
## [22,] 1.18913493 1.152611318 -1.229687900 0.80017955 -0.56489096
## [23,] 1.10207869 1.990447711 1.103843700 -0.90463948 0.37860479
## [24,] 0.84375186 0.443129252 0.044718265 2.12747244 -0.91527479
## [25,] 1.09271657 -0.327857012 -1.178681945 0.46252359 0.11107310
## [26,] -1.17698455 0.578467730 0.488499429 0.46083460 -0.85613882
## [27,] -3.51327134 0.029403846 0.079118367 -0.11974897 -0.64637037
## [28,] -2.00742851 1.021839777 0.394554296 0.87434621 0.38150903
## [29,] 0.75405816 1.320864558 0.583881320 -1.51903635 0.43081174
## [30,] -0.41081838 1.594592945 -0.015513150 0.08669149 1.24694561
## [31,] 0.91507627 0.452777170 0.628698324 0.86731433 -0.50191633
## [32,] 0.38563369 1.174537769 -0.609697508 1.21934287 0.40267127
## [33,] 1.29735335 1.274193509 -2.787306980 0.74032020 -0.22833770
## [34,] 0.02912683 1.269229311 -0.421688431 1.27602068 0.63832352
## [35,] -0.20371592 -2.047789461 -0.132058791 -0.32461390 0.00206257
## [36,] 1.04526771 1.080516067 -0.025853674 1.05168533 -0.58703027
## [37,] 0.74583126 -0.910930878 0.921503195 0.11828948 -0.32410974
## [38,] 0.70101817 -2.650779135 0.988768319 0.02025054 0.72624775
## [39,] 0.82661712 -1.011545574 0.880827221 0.69804918 0.24935972
## [40,] -1.67657269 1.825686539 -0.127783552 1.84220975 2.45091302
## [41,] 0.95824757 1.177397362 0.915280084 1.35710490 -0.62433573
## [42,] 0.89611874 0.183038328 0.734262858 0.73616427 -0.46782268
## [43,] -0.68833634 -2.040932214 0.046964327 -0.48974400 -0.33368164
## [44,] 1.49460068 1.884385329 -0.899041622 -1.48520245 0.22774102
## [45,] 1.29556645 1.396919305 0.614880751 -1.31698463 0.32463972
## [46,] -4.98245786 0.883279794 -0.015107498 0.33112582 0.34982133
## [47,] -8.18928009 0.276323519 -0.324657487 -0.72788703 -0.85910327
## [48,] -2.32665160 -1.500588886 0.049184340 -0.77338331 -1.25307942
## [49,] -0.28572340 -0.711276268 0.343319526 -0.17579461 -0.83017355
## [50,] 0.54353487 -0.157732499 0.287556699 0.38957260 -0.40598538
## [51,] -1.17727348 -1.695882839 0.095551719 -0.43759344 -0.57428723
## [52,] 1.00639239 0.591529008 -0.784521496 0.61618569 -0.43398596
## [53,] 0.99461695 0.969737867 0.405805032 1.17840519 -0.51169724
## [54,] 1.18789859 1.233989422 1.228574665 -1.45317358 0.16909789
## [55,] 1.27525363 1.207714155 0.537632322 -1.63283374 0.19206799
## [56,] -0.01711482 0.067301016 0.204491050 0.72857979 0.02439764
## [57,] 0.93658622 -0.674930875 1.381106042 -0.62012643 0.43686938
## [58,] 0.78648437 -1.396727926 0.673371568 0.06453782 0.01182713
## [59,] -0.06164582 0.098098313 0.194456604 0.74285550 0.04402483
## [60,] -0.99233726 -1.783806938 0.118654846 -0.40359492 -0.46347685
## [61,] -0.50374652 -2.021079162 0.174313800 -0.38296435 -0.22975451
## [62,] -3.39678247 -0.287675556 0.140609459 -0.42146824 -1.18977791
## [63,] -8.14606670 0.255595618 -0.314781484 -0.74424191 -0.90920968
## [64,] 0.99935433 -2.699945998 -3.500301822 -0.09739909 0.13137505
## [65,] -1.86108171 0.923752887 0.311846407 0.86523304 0.38930735
## [66,] 1.36528966 1.474246532 0.007761244 -1.52183727 0.24208357
## [67,] 1.03501976 0.498364126 -0.303479934 0.62722988 -0.50986811
## [68,] 0.48974173 -0.257828581 -0.574851443 0.43882023 -0.11509535
## [69,] 0.75392557 0.631779084 0.568889731 0.90715404 -0.50318884
## [70,] -6.79499501 0.617747451 -0.179093152 -0.26291880 -0.36499145
## [71,] 0.77566634 -3.490118820 -0.111388368 -0.18905373 1.36386854
## [72,] 1.00989457 1.053568141 0.441819916 1.15538265 -0.61309039
## [73,] 0.94354352 0.274238088 1.064294194 -0.71124425 -0.19354888
## [74,] 0.54637338 -0.353732914 -0.858807909 0.39748652 0.05193908
## [75,] 1.05388361 0.601339536 0.830967959 -0.54366263 -0.20511638
## [76,] 0.92511228 -2.027965257 -2.853078692 0.27410706 -0.17270481
## [77,] 1.35231581 -0.371953537 -3.972212031 -0.55881297 -0.03386430
## [78,] 0.98950919 0.425804479 0.090467434 0.69060911 -0.50599432
## [79,] 0.78696203 -1.026786429 0.454636665 0.04342714 -0.21407823
## [80,] 0.94128374 -0.834662949 1.168280568 -0.46256411 0.72792132
## [81,] -1.80861589 1.791255335 -0.129650486 1.77015986 2.34710083
## [82,] 1.30702700 1.718469106 0.728980808 -1.23936584 0.14141492
## [83,] 0.90739332 -1.574890844 -0.543716880 0.19415965 0.56760519
## [84,] 0.67451450 0.009880666 0.706615898 -0.84430459 -0.14310196
## [85,] 0.86921852 -0.052513648 0.682425704 0.80942896 -0.22628595
## [86,] -1.15213321 -2.111471625 -0.217356353 -0.83420212 -0.68868662
## [87,] 1.04205363 1.149307455 1.034885749 -1.52695640 0.31764966
## [88,] -1.31736183 0.200372728 0.806530021 -0.96222210 -0.29665932
## [89,] 0.88539344 0.418147836 0.445248112 0.76400757 -0.48491910
## [90,] 0.92677427 -0.418702983 0.328830025 0.66250749 -0.03098680
## [91,] 1.58666035 1.808249724 -1.852704492 -1.73433661 0.30359567
## [92,] -1.36713567 -1.997667664 -0.264589114 -0.87281758 -0.79923591
## [93,] -1.36728529 -1.997636883 -0.264602888 -0.87280944 -0.79917107
## [94,] 0.90175176 -1.254160623 -0.487823212 0.27357713 0.41242286
## [95,] 1.06942899 0.981647320 -0.182946814 0.98974609 -0.55090530
## [96,] 1.02680348 1.185885841 0.080587587 1.11824570 -0.60942400
## [97,] -1.50954045 0.773317319 0.433398585 0.68233700 -0.14006415
## [98,] 0.70518327 1.377678619 0.545541374 -1.49019553 0.46278614
## [99,] -0.03801752 0.077024260 0.192516360 0.73568852 0.04152618
## [100,] 0.55123792 -0.365756010 -0.837887622 0.40132551 0.05744330
## [101,] 0.83586673 -2.419562284 0.537798455 0.48422079 1.08969796
## [102,] -1.31736183 0.200372728 0.806530021 -0.96222210 -0.29665932
## [103,] -1.36728529 -1.997636883 -0.264602888 -0.87280944 -0.79917107
## [104,] 1.24034059 1.263690131 0.608220009 -1.57928506 0.19217680
## [105,] -2.47679713 0.797741240 0.118592541 0.73909782 0.49111514
## [106,] 1.64621786 1.709957952 -2.552686543 -1.98970947 0.32473585
## [107,] -10.83087965 1.407878649 -0.663246439 0.13355018 2.00966079
## [,6] [,7] [,8] [,9]
## [1,] -0.292710567 -0.027773771 1.039070e-03 -6.157092e-03
## [2,] -0.215118307 -0.085281355 -2.069443e-03 3.102947e-02
## [3,] -0.028622391 -0.100124793 -5.692688e-03 -9.523159e-03
## [4,] 0.269466697 0.000333514 -8.494862e-03 -1.366867e-02
## [5,] -1.299781463 0.409028715 2.367783e-02 1.969602e-03
## [6,] -0.418854805 -0.088631244 -1.040480e-03 2.380696e-03
## [7,] 0.329526993 0.241877460 -6.403652e-03 -2.230099e-03
## [8,] 0.904903840 0.190233353 -6.970243e-03 6.433120e-03
## [9,] -0.193267467 -0.034032549 -6.916182e-04 -1.433690e-02
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## [79,] 1.039286135 0.121918764 -5.382141e-03 9.109819e-03
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