Implementasi Principal Component Analysis (PCA) dan Factor Analysis (FA) pada Risiko Perilaku Kanker Serviks
Aida Zahira(106) dan Fauziah Roikhana W. (162)
2026-03-03
library(psych)
library(REdaS)## Loading required package: gridlibrary(factoextra)## Loading required package: ggplot2##
## Attaching package: 'ggplot2'## The following objects are masked from 'package:psych':
##
## %+%, alpha## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBalibrary(sjPlot)##
## Attaching package: 'sjPlot'## The following object is masked from 'package:ggplot2':
##
## set_themelibrary(ppcor)## Loading required package: MASSdata <- read.csv("C:\\Users\\zahir\\Downloads\\Cervical Cancer Behavior Risk.csv")
data## behavior_sexualRisk behavior_eating behavior_personalHygine
## 1 10 13 12
## 2 10 11 11
## 3 10 15 3
## 4 10 11 10
## 5 8 11 7
## 6 10 14 8
## 7 10 15 4
## 8 8 12 9
## 9 10 15 7
## 10 7 15 7
## 11 7 15 7
## 12 10 15 8
## 13 10 15 12
## 14 9 12 14
## 15 2 15 15
## 16 10 15 7
## 17 10 15 9
## 18 10 12 7
## 19 10 11 12
## 20 10 12 12
## 21 10 15 15
## 22 10 12 11
## 23 10 13 14
## 24 10 15 13
## 25 10 12 10
## 26 10 15 13
## 27 10 13 15
## 28 10 15 11
## 29 10 11 11
## 30 10 14 10
## 31 10 8 9
## 32 10 15 15
## 33 10 10 11
## 34 10 11 10
## 35 10 15 15
## 36 10 3 5
## 37 10 15 9
## 38 10 10 12
## 39 10 9 11
## 40 10 14 14
## 41 10 12 11
## 42 10 15 13
## 43 10 15 15
## 44 10 15 15
## 45 10 11 14
## 46 10 15 14
## 47 10 14 11
## 48 10 15 15
## 49 10 15 11
## 50 6 15 11
## 51 10 11 15
## 52 10 15 15
## 53 10 9 12
## 54 10 13 12
## 55 10 15 15
## 56 10 9 8
## 57 10 10 5
## 58 10 11 8
## 59 10 11 9
## 60 10 13 9
## 61 10 12 10
## 62 10 10 10
## 63 10 13 11
## 64 10 13 15
## 65 10 15 8
## 66 10 13 11
## 67 10 12 13
## 68 10 14 14
## 69 10 12 15
## 70 10 8 11
## 71 9 12 13
## 72 10 14 14
## intention_aggregation intention_commitment attitude_consistency
## 1 4 7 9
## 2 10 14 7
## 3 2 14 8
## 4 10 15 7
## 5 8 10 7
## 6 6 15 8
## 7 6 14 6
## 8 10 10 5
## 9 2 15 6
## 10 6 11 8
## 11 10 14 7
## 12 9 15 7
## 13 10 15 6
## 14 9 15 10
## 15 6 13 8
## 16 6 14 8
## 17 7 6 8
## 18 5 10 8
## 19 2 10 8
## 20 8 10 8
## 21 4 15 8
## 22 10 15 7
## 23 10 15 6
## 24 10 15 2
## 25 7 15 6
## 26 10 15 6
## 27 8 13 7
## 28 10 15 8
## 29 10 14 5
## 30 9 15 4
## 31 10 15 10
## 32 8 9 8
## 33 10 15 5
## 34 9 15 5
## 35 10 15 10
## 36 2 9 6
## 37 3 15 8
## 38 5 7 6
## 39 10 15 7
## 40 10 11 5
## 41 10 15 7
## 42 10 15 6
## 43 10 15 8
## 44 10 15 9
## 45 10 15 10
## 46 10 11 10
## 47 10 15 9
## 48 6 11 7
## 49 10 15 8
## 50 10 12 8
## 51 10 11 6
## 52 10 15 10
## 53 10 14 9
## 54 2 15 7
## 55 10 11 7
## 56 2 15 6
## 57 2 15 8
## 58 10 15 7
## 59 6 15 6
## 60 10 15 8
## 61 10 15 6
## 62 10 15 6
## 63 6 15 8
## 64 10 15 8
## 65 6 11 6
## 66 6 14 9
## 67 10 11 7
## 68 10 15 6
## 69 10 15 8
## 70 6 10 6
## 71 10 13 6
## 72 6 12 7
## attitude_spontaneity norm_significantPerson norm_fulfillment
## 1 10 1 8
## 2 7 5 5
## 3 10 1 4
## 4 7 1 5
## 5 8 1 5
## 6 10 1 3
## 7 10 5 3
## 8 10 5 5
## 9 10 1 3
## 10 8 5 3
## 11 9 1 3
## 12 10 1 3
## 13 10 1 3
## 14 9 3 6
## 15 9 1 3
## 16 8 4 8
## 17 8 1 12
## 18 8 1 8
## 19 8 2 10
## 20 6 2 7
## 21 10 5 3
## 22 8 3 3
## 23 8 1 5
## 24 10 1 5
## 25 8 2 4
## 26 10 1 3
## 27 8 3 5
## 28 10 1 3
## 29 8 1 4
## 30 5 2 5
## 31 10 1 3
## 32 9 4 7
## 33 8 1 5
## 34 10 3 3
## 35 10 1 3
## 36 10 1 3
## 37 10 1 3
## 38 6 4 5
## 39 6 1 3
## 40 9 1 5
## 41 8 3 3
## 42 10 1 7
## 43 8 5 11
## 44 10 5 11
## 45 10 5 15
## 46 8 5 11
## 47 10 5 15
## 48 6 5 11
## 49 10 1 15
## 50 10 5 14
## 51 10 5 15
## 52 10 5 15
## 53 6 5 11
## 54 10 5 15
## 55 8 5 15
## 56 10 1 15
## 57 10 5 13
## 58 8 5 14
## 59 8 5 14
## 60 8 5 14
## 61 8 5 15
## 62 6 5 14
## 63 10 5 15
## 64 10 5 14
## 65 10 5 11
## 66 10 5 15
## 67 7 5 14
## 68 7 5 15
## 69 8 5 15
## 70 4 3 13
## 71 6 5 14
## 72 8 5 15
## perception_vulnerability perception_severity motivation_strength
## 1 7 3 14
## 2 4 2 15
## 3 7 2 7
## 4 4 2 15
## 5 3 2 15
## 6 4 2 14
## 7 7 2 7
## 8 5 2 10
## 9 5 2 9
## 10 3 4 15
## 11 8 2 4
## 12 7 2 15
## 13 3 2 4
## 14 3 2 15
## 15 3 4 15
## 16 10 2 3
## 17 5 4 5
## 18 10 4 6
## 19 8 7 6
## 20 6 2 12
## 21 8 3 11
## 22 3 2 13
## 23 5 2 15
## 24 6 2 14
## 25 9 2 15
## 26 5 2 15
## 27 9 2 13
## 28 3 2 15
## 29 3 4 15
## 30 7 3 10
## 31 3 2 15
## 32 6 4 12
## 33 3 6 15
## 34 3 2 11
## 35 3 2 15
## 36 9 6 11
## 37 5 6 10
## 38 10 4 11
## 39 6 2 15
## 40 4 2 14
## 41 4 2 14
## 42 7 2 15
## 43 15 10 15
## 44 15 10 15
## 45 14 10 15
## 46 15 10 15
## 47 15 10 15
## 48 13 10 15
## 49 15 10 15
## 50 13 10 15
## 51 11 10 15
## 52 14 9 9
## 53 11 9 15
## 54 10 2 15
## 55 13 10 15
## 56 15 8 11
## 57 15 10 15
## 58 13 8 12
## 59 11 8 11
## 60 8 8 11
## 61 11 8 13
## 62 13 9 15
## 63 7 10 13
## 64 6 8 13
## 65 15 8 15
## 66 15 10 15
## 67 15 9 14
## 68 14 10 15
## 69 14 8 12
## 70 9 8 14
## 71 13 10 13
## 72 12 10 10
## motivation_willingness socialSupport_emotionality socialSupport_appreciation
## 1 8 5 7
## 2 13 7 6
## 3 3 3 6
## 4 13 7 4
## 5 5 3 6
## 6 8 7 2
## 7 13 3 3
## 8 9 13 2
## 9 15 13 10
## 10 3 8 2
## 11 3 7 9
## 12 3 3 6
## 13 3 3 2
## 14 15 3 10
## 15 3 7 6
## 16 3 3 2
## 17 4 3 3
## 18 3 3 2
## 19 5 3 2
## 20 11 9 8
## 21 3 3 2
## 22 11 10 7
## 23 10 12 8
## 24 14 14 8
## 25 12 10 7
## 26 13 9 7
## 27 11 12 9
## 28 13 13 10
## 29 11 13 9
## 30 7 4 6
## 31 13 11 6
## 32 12 14 9
## 33 13 13 10
## 34 11 9 4
## 35 10 10 10
## 36 10 9 9
## 37 15 13 10
## 38 9 11 8
## 39 15 15 10
## 40 15 11 8
## 41 7 9 8
## 42 7 3 4
## 43 15 15 10
## 44 15 15 10
## 45 9 9 4
## 46 15 15 10
## 47 13 6 6
## 48 15 11 10
## 49 13 3 2
## 50 7 5 2
## 51 15 15 6
## 52 13 12 9
## 53 11 3 2
## 54 12 11 7
## 55 15 11 8
## 56 11 13 10
## 57 3 3 2
## 58 7 4 3
## 59 7 3 2
## 60 3 3 2
## 61 7 3 2
## 62 9 13 8
## 63 7 3 5
## 64 7 3 4
## 65 7 3 4
## 66 3 3 4
## 67 10 6 6
## 68 13 9 8
## 69 14 11 7
## 70 12 9 7
## 71 12 11 8
## 72 13 11 9
## socialSupport_instrumental empowerment_knowledge empowerment_abilities
## 1 12 12 11
## 2 5 5 4
## 3 11 3 3
## 4 4 4 4
## 5 12 5 4
## 6 7 13 9
## 7 15 3 3
## 8 9 8 7
## 9 15 13 15
## 10 9 3 4
## 11 13 8 3
## 12 13 7 5
## 13 15 13 6
## 14 15 11 3
## 15 7 7 7
## 16 5 5 5
## 17 5 7 7
## 18 4 4 3
## 19 4 4 4
## 20 12 10 10
## 21 7 8 5
## 22 12 12 12
## 23 15 15 15
## 24 14 15 14
## 25 12 14 10
## 26 12 15 11
## 27 10 12 13
## 28 15 15 13
## 29 13 13 12
## 30 7 5 9
## 31 15 15 10
## 32 14 13 9
## 33 15 13 13
## 34 9 15 15
## 35 15 15 15
## 36 14 6 10
## 37 15 15 15
## 38 11 11 10
## 39 15 15 15
## 40 14 13 13
## 41 12 15 10
## 42 3 11 5
## 43 15 15 15
## 44 15 15 15
## 45 3 14 11
## 46 15 15 15
## 47 12 15 11
## 48 15 11 11
## 49 9 15 8
## 50 5 13 9
## 51 9 15 15
## 52 15 15 15
## 53 6 13 7
## 54 6 10 9
## 55 15 15 13
## 56 15 13 13
## 57 13 15 15
## 58 3 4 4
## 59 3 3 3
## 60 3 3 3
## 61 3 3 3
## 62 14 13 12
## 63 3 3 3
## 64 3 3 6
## 65 11 13 10
## 66 7 7 7
## 67 6 9 7
## 68 12 12 11
## 69 13 15 11
## 70 11 12 10
## 71 12 11 13
## 72 14 13 15
## empowerment_desires ca_cervix
## 1 8 1
## 2 4 1
## 3 15 1
## 4 4 1
## 5 7 1
## 6 6 1
## 7 5 1
## 8 12 1
## 9 15 1
## 10 4 1
## 11 9 1
## 12 9 1
## 13 11 1
## 14 11 1
## 15 3 1
## 16 3 1
## 17 3 1
## 18 5 1
## 19 3 1
## 20 9 1
## 21 3 1
## 22 12 0
## 23 15 0
## 24 15 0
## 25 14 0
## 26 15 0
## 27 12 0
## 28 15 0
## 29 13 0
## 30 12 0
## 31 15 0
## 32 12 0
## 33 13 0
## 34 15 0
## 35 15 0
## 36 10 0
## 37 15 0
## 38 11 0
## 39 14 0
## 40 13 0
## 41 14 0
## 42 9 0
## 43 15 0
## 44 15 0
## 45 15 0
## 46 15 0
## 47 14 0
## 48 15 0
## 49 11 0
## 50 3 0
## 51 9 0
## 52 15 0
## 53 3 0
## 54 12 0
## 55 11 0
## 56 10 0
## 57 15 0
## 58 7 0
## 59 3 0
## 60 3 0
## 61 3 0
## 62 12 0
## 63 3 0
## 64 3 0
## 65 15 0
## 66 11 0
## 67 11 0
## 68 9 0
## 69 14 0
## 70 10 0
## 71 15 0
## 72 15 0dim(data)## [1] 72 20str(data)## 'data.frame': 72 obs. of 20 variables:
## $ behavior_sexualRisk : int 10 10 10 10 8 10 10 8 10 7 ...
## $ behavior_eating : int 13 11 15 11 11 14 15 12 15 15 ...
## $ behavior_personalHygine : int 12 11 3 10 7 8 4 9 7 7 ...
## $ intention_aggregation : int 4 10 2 10 8 6 6 10 2 6 ...
## $ intention_commitment : int 7 14 14 15 10 15 14 10 15 11 ...
## $ attitude_consistency : int 9 7 8 7 7 8 6 5 6 8 ...
## $ attitude_spontaneity : int 10 7 10 7 8 10 10 10 10 8 ...
## $ norm_significantPerson : int 1 5 1 1 1 1 5 5 1 5 ...
## $ norm_fulfillment : int 8 5 4 5 5 3 3 5 3 3 ...
## $ perception_vulnerability : int 7 4 7 4 3 4 7 5 5 3 ...
## $ perception_severity : int 3 2 2 2 2 2 2 2 2 4 ...
## $ motivation_strength : int 14 15 7 15 15 14 7 10 9 15 ...
## $ motivation_willingness : int 8 13 3 13 5 8 13 9 15 3 ...
## $ socialSupport_emotionality: int 5 7 3 7 3 7 3 13 13 8 ...
## $ socialSupport_appreciation: int 7 6 6 4 6 2 3 2 10 2 ...
## $ socialSupport_instrumental: int 12 5 11 4 12 7 15 9 15 9 ...
## $ empowerment_knowledge : int 12 5 3 4 5 13 3 8 13 3 ...
## $ empowerment_abilities : int 11 4 3 4 4 9 3 7 15 4 ...
## $ empowerment_desires : int 8 4 15 4 7 6 5 12 15 4 ...
## $ ca_cervix : int 1 1 1 1 1 1 1 1 1 1 ...summary(data)## behavior_sexualRisk behavior_eating behavior_personalHygine
## Min. : 2.000 Min. : 3.00 Min. : 3.00
## 1st Qu.:10.000 1st Qu.:11.00 1st Qu.: 9.00
## Median :10.000 Median :13.00 Median :11.00
## Mean : 9.667 Mean :12.79 Mean :11.08
## 3rd Qu.:10.000 3rd Qu.:15.00 3rd Qu.:14.00
## Max. :10.000 Max. :15.00 Max. :15.00
## intention_aggregation intention_commitment attitude_consistency
## Min. : 2.000 Min. : 6.00 Min. : 2.000
## 1st Qu.: 6.000 1st Qu.:11.00 1st Qu.: 6.000
## Median :10.000 Median :15.00 Median : 7.000
## Mean : 7.903 Mean :13.35 Mean : 7.181
## 3rd Qu.:10.000 3rd Qu.:15.00 3rd Qu.: 8.000
## Max. :10.000 Max. :15.00 Max. :10.000
## attitude_spontaneity norm_significantPerson norm_fulfillment
## Min. : 4.000 Min. :1.000 Min. : 3.000
## 1st Qu.: 8.000 1st Qu.:1.000 1st Qu.: 3.000
## Median : 9.000 Median :3.000 Median : 7.000
## Mean : 8.611 Mean :3.125 Mean : 8.486
## 3rd Qu.:10.000 3rd Qu.:5.000 3rd Qu.:14.000
## Max. :10.000 Max. :5.000 Max. :15.000
## perception_vulnerability perception_severity motivation_strength
## Min. : 3.000 Min. : 2.000 Min. : 3.00
## 1st Qu.: 5.000 1st Qu.: 2.000 1st Qu.:11.00
## Median : 8.000 Median : 4.000 Median :14.00
## Mean : 8.514 Mean : 5.389 Mean :12.65
## 3rd Qu.:13.000 3rd Qu.: 9.000 3rd Qu.:15.00
## Max. :15.000 Max. :10.000 Max. :15.00
## motivation_willingness socialSupport_emotionality socialSupport_appreciation
## Min. : 3.000 Min. : 3.000 Min. : 2.000
## 1st Qu.: 7.000 1st Qu.: 3.000 1st Qu.: 3.750
## Median :11.000 Median : 9.000 Median : 6.500
## Mean : 9.694 Mean : 8.097 Mean : 6.167
## 3rd Qu.:13.000 3rd Qu.:11.250 3rd Qu.: 9.000
## Max. :15.000 Max. :15.000 Max. :10.000
## socialSupport_instrumental empowerment_knowledge empowerment_abilities
## Min. : 3.00 Min. : 3.00 Min. : 3.000
## 1st Qu.: 6.75 1st Qu.: 7.00 1st Qu.: 5.000
## Median :12.00 Median :12.00 Median :10.000
## Mean :10.38 Mean :10.54 Mean : 9.319
## 3rd Qu.:14.25 3rd Qu.:15.00 3rd Qu.:13.000
## Max. :15.00 Max. :15.00 Max. :15.000
## empowerment_desires ca_cervix
## Min. : 3.00 Min. :0.0000
## 1st Qu.: 6.75 1st Qu.:0.0000
## Median :11.00 Median :0.0000
## Mean :10.28 Mean :0.2917
## 3rd Qu.:15.00 3rd Qu.:1.0000
## Max. :15.00 Max. :1.0000data_pca <- subset(data, select = -ca_cervix)
data_pca## behavior_sexualRisk behavior_eating behavior_personalHygine
## 1 10 13 12
## 2 10 11 11
## 3 10 15 3
## 4 10 11 10
## 5 8 11 7
## 6 10 14 8
## 7 10 15 4
## 8 8 12 9
## 9 10 15 7
## 10 7 15 7
## 11 7 15 7
## 12 10 15 8
## 13 10 15 12
## 14 9 12 14
## 15 2 15 15
## 16 10 15 7
## 17 10 15 9
## 18 10 12 7
## 19 10 11 12
## 20 10 12 12
## 21 10 15 15
## 22 10 12 11
## 23 10 13 14
## 24 10 15 13
## 25 10 12 10
## 26 10 15 13
## 27 10 13 15
## 28 10 15 11
## 29 10 11 11
## 30 10 14 10
## 31 10 8 9
## 32 10 15 15
## 33 10 10 11
## 34 10 11 10
## 35 10 15 15
## 36 10 3 5
## 37 10 15 9
## 38 10 10 12
## 39 10 9 11
## 40 10 14 14
## 41 10 12 11
## 42 10 15 13
## 43 10 15 15
## 44 10 15 15
## 45 10 11 14
## 46 10 15 14
## 47 10 14 11
## 48 10 15 15
## 49 10 15 11
## 50 6 15 11
## 51 10 11 15
## 52 10 15 15
## 53 10 9 12
## 54 10 13 12
## 55 10 15 15
## 56 10 9 8
## 57 10 10 5
## 58 10 11 8
## 59 10 11 9
## 60 10 13 9
## 61 10 12 10
## 62 10 10 10
## 63 10 13 11
## 64 10 13 15
## 65 10 15 8
## 66 10 13 11
## 67 10 12 13
## 68 10 14 14
## 69 10 12 15
## 70 10 8 11
## 71 9 12 13
## 72 10 14 14
## intention_aggregation intention_commitment attitude_consistency
## 1 4 7 9
## 2 10 14 7
## 3 2 14 8
## 4 10 15 7
## 5 8 10 7
## 6 6 15 8
## 7 6 14 6
## 8 10 10 5
## 9 2 15 6
## 10 6 11 8
## 11 10 14 7
## 12 9 15 7
## 13 10 15 6
## 14 9 15 10
## 15 6 13 8
## 16 6 14 8
## 17 7 6 8
## 18 5 10 8
## 19 2 10 8
## 20 8 10 8
## 21 4 15 8
## 22 10 15 7
## 23 10 15 6
## 24 10 15 2
## 25 7 15 6
## 26 10 15 6
## 27 8 13 7
## 28 10 15 8
## 29 10 14 5
## 30 9 15 4
## 31 10 15 10
## 32 8 9 8
## 33 10 15 5
## 34 9 15 5
## 35 10 15 10
## 36 2 9 6
## 37 3 15 8
## 38 5 7 6
## 39 10 15 7
## 40 10 11 5
## 41 10 15 7
## 42 10 15 6
## 43 10 15 8
## 44 10 15 9
## 45 10 15 10
## 46 10 11 10
## 47 10 15 9
## 48 6 11 7
## 49 10 15 8
## 50 10 12 8
## 51 10 11 6
## 52 10 15 10
## 53 10 14 9
## 54 2 15 7
## 55 10 11 7
## 56 2 15 6
## 57 2 15 8
## 58 10 15 7
## 59 6 15 6
## 60 10 15 8
## 61 10 15 6
## 62 10 15 6
## 63 6 15 8
## 64 10 15 8
## 65 6 11 6
## 66 6 14 9
## 67 10 11 7
## 68 10 15 6
## 69 10 15 8
## 70 6 10 6
## 71 10 13 6
## 72 6 12 7
## attitude_spontaneity norm_significantPerson norm_fulfillment
## 1 10 1 8
## 2 7 5 5
## 3 10 1 4
## 4 7 1 5
## 5 8 1 5
## 6 10 1 3
## 7 10 5 3
## 8 10 5 5
## 9 10 1 3
## 10 8 5 3
## 11 9 1 3
## 12 10 1 3
## 13 10 1 3
## 14 9 3 6
## 15 9 1 3
## 16 8 4 8
## 17 8 1 12
## 18 8 1 8
## 19 8 2 10
## 20 6 2 7
## 21 10 5 3
## 22 8 3 3
## 23 8 1 5
## 24 10 1 5
## 25 8 2 4
## 26 10 1 3
## 27 8 3 5
## 28 10 1 3
## 29 8 1 4
## 30 5 2 5
## 31 10 1 3
## 32 9 4 7
## 33 8 1 5
## 34 10 3 3
## 35 10 1 3
## 36 10 1 3
## 37 10 1 3
## 38 6 4 5
## 39 6 1 3
## 40 9 1 5
## 41 8 3 3
## 42 10 1 7
## 43 8 5 11
## 44 10 5 11
## 45 10 5 15
## 46 8 5 11
## 47 10 5 15
## 48 6 5 11
## 49 10 1 15
## 50 10 5 14
## 51 10 5 15
## 52 10 5 15
## 53 6 5 11
## 54 10 5 15
## 55 8 5 15
## 56 10 1 15
## 57 10 5 13
## 58 8 5 14
## 59 8 5 14
## 60 8 5 14
## 61 8 5 15
## 62 6 5 14
## 63 10 5 15
## 64 10 5 14
## 65 10 5 11
## 66 10 5 15
## 67 7 5 14
## 68 7 5 15
## 69 8 5 15
## 70 4 3 13
## 71 6 5 14
## 72 8 5 15
## perception_vulnerability perception_severity motivation_strength
## 1 7 3 14
## 2 4 2 15
## 3 7 2 7
## 4 4 2 15
## 5 3 2 15
## 6 4 2 14
## 7 7 2 7
## 8 5 2 10
## 9 5 2 9
## 10 3 4 15
## 11 8 2 4
## 12 7 2 15
## 13 3 2 4
## 14 3 2 15
## 15 3 4 15
## 16 10 2 3
## 17 5 4 5
## 18 10 4 6
## 19 8 7 6
## 20 6 2 12
## 21 8 3 11
## 22 3 2 13
## 23 5 2 15
## 24 6 2 14
## 25 9 2 15
## 26 5 2 15
## 27 9 2 13
## 28 3 2 15
## 29 3 4 15
## 30 7 3 10
## 31 3 2 15
## 32 6 4 12
## 33 3 6 15
## 34 3 2 11
## 35 3 2 15
## 36 9 6 11
## 37 5 6 10
## 38 10 4 11
## 39 6 2 15
## 40 4 2 14
## 41 4 2 14
## 42 7 2 15
## 43 15 10 15
## 44 15 10 15
## 45 14 10 15
## 46 15 10 15
## 47 15 10 15
## 48 13 10 15
## 49 15 10 15
## 50 13 10 15
## 51 11 10 15
## 52 14 9 9
## 53 11 9 15
## 54 10 2 15
## 55 13 10 15
## 56 15 8 11
## 57 15 10 15
## 58 13 8 12
## 59 11 8 11
## 60 8 8 11
## 61 11 8 13
## 62 13 9 15
## 63 7 10 13
## 64 6 8 13
## 65 15 8 15
## 66 15 10 15
## 67 15 9 14
## 68 14 10 15
## 69 14 8 12
## 70 9 8 14
## 71 13 10 13
## 72 12 10 10
## motivation_willingness socialSupport_emotionality socialSupport_appreciation
## 1 8 5 7
## 2 13 7 6
## 3 3 3 6
## 4 13 7 4
## 5 5 3 6
## 6 8 7 2
## 7 13 3 3
## 8 9 13 2
## 9 15 13 10
## 10 3 8 2
## 11 3 7 9
## 12 3 3 6
## 13 3 3 2
## 14 15 3 10
## 15 3 7 6
## 16 3 3 2
## 17 4 3 3
## 18 3 3 2
## 19 5 3 2
## 20 11 9 8
## 21 3 3 2
## 22 11 10 7
## 23 10 12 8
## 24 14 14 8
## 25 12 10 7
## 26 13 9 7
## 27 11 12 9
## 28 13 13 10
## 29 11 13 9
## 30 7 4 6
## 31 13 11 6
## 32 12 14 9
## 33 13 13 10
## 34 11 9 4
## 35 10 10 10
## 36 10 9 9
## 37 15 13 10
## 38 9 11 8
## 39 15 15 10
## 40 15 11 8
## 41 7 9 8
## 42 7 3 4
## 43 15 15 10
## 44 15 15 10
## 45 9 9 4
## 46 15 15 10
## 47 13 6 6
## 48 15 11 10
## 49 13 3 2
## 50 7 5 2
## 51 15 15 6
## 52 13 12 9
## 53 11 3 2
## 54 12 11 7
## 55 15 11 8
## 56 11 13 10
## 57 3 3 2
## 58 7 4 3
## 59 7 3 2
## 60 3 3 2
## 61 7 3 2
## 62 9 13 8
## 63 7 3 5
## 64 7 3 4
## 65 7 3 4
## 66 3 3 4
## 67 10 6 6
## 68 13 9 8
## 69 14 11 7
## 70 12 9 7
## 71 12 11 8
## 72 13 11 9
## socialSupport_instrumental empowerment_knowledge empowerment_abilities
## 1 12 12 11
## 2 5 5 4
## 3 11 3 3
## 4 4 4 4
## 5 12 5 4
## 6 7 13 9
## 7 15 3 3
## 8 9 8 7
## 9 15 13 15
## 10 9 3 4
## 11 13 8 3
## 12 13 7 5
## 13 15 13 6
## 14 15 11 3
## 15 7 7 7
## 16 5 5 5
## 17 5 7 7
## 18 4 4 3
## 19 4 4 4
## 20 12 10 10
## 21 7 8 5
## 22 12 12 12
## 23 15 15 15
## 24 14 15 14
## 25 12 14 10
## 26 12 15 11
## 27 10 12 13
## 28 15 15 13
## 29 13 13 12
## 30 7 5 9
## 31 15 15 10
## 32 14 13 9
## 33 15 13 13
## 34 9 15 15
## 35 15 15 15
## 36 14 6 10
## 37 15 15 15
## 38 11 11 10
## 39 15 15 15
## 40 14 13 13
## 41 12 15 10
## 42 3 11 5
## 43 15 15 15
## 44 15 15 15
## 45 3 14 11
## 46 15 15 15
## 47 12 15 11
## 48 15 11 11
## 49 9 15 8
## 50 5 13 9
## 51 9 15 15
## 52 15 15 15
## 53 6 13 7
## 54 6 10 9
## 55 15 15 13
## 56 15 13 13
## 57 13 15 15
## 58 3 4 4
## 59 3 3 3
## 60 3 3 3
## 61 3 3 3
## 62 14 13 12
## 63 3 3 3
## 64 3 3 6
## 65 11 13 10
## 66 7 7 7
## 67 6 9 7
## 68 12 12 11
## 69 13 15 11
## 70 11 12 10
## 71 12 11 13
## 72 14 13 15
## empowerment_desires
## 1 8
## 2 4
## 3 15
## 4 4
## 5 7
## 6 6
## 7 5
## 8 12
## 9 15
## 10 4
## 11 9
## 12 9
## 13 11
## 14 11
## 15 3
## 16 3
## 17 3
## 18 5
## 19 3
## 20 9
## 21 3
## 22 12
## 23 15
## 24 15
## 25 14
## 26 15
## 27 12
## 28 15
## 29 13
## 30 12
## 31 15
## 32 12
## 33 13
## 34 15
## 35 15
## 36 10
## 37 15
## 38 11
## 39 14
## 40 13
## 41 14
## 42 9
## 43 15
## 44 15
## 45 15
## 46 15
## 47 14
## 48 15
## 49 11
## 50 3
## 51 9
## 52 15
## 53 3
## 54 12
## 55 11
## 56 10
## 57 15
## 58 7
## 59 3
## 60 3
## 61 3
## 62 12
## 63 3
## 64 3
## 65 15
## 66 11
## 67 11
## 68 9
## 69 14
## 70 10
## 71 15
## 72 15colnames(data_pca) <- paste0("X", 1:ncol(data_pca))
data_scaled <- scale(data_pca)
data_scaled #biar skalanya sama maka di standarisasi## X1 X2 X3 X4 X5 X6
## 1 0.2808717 0.0882285 0.30214667 -1.42533462 -2.6730651 1.1947676
## 2 0.2808717 -0.7587651 -0.02746788 0.76592714 0.2749104 -0.1185647
## 3 0.2808717 0.9352221 -2.66438430 -2.15575520 0.2749104 0.5381014
## 4 0.2808717 -0.7587651 -0.35708243 0.76592714 0.6960498 -0.1185647
## 5 -1.4043583 -0.7587651 -1.34592609 0.03550656 -1.4096470 -0.1185647
## 6 0.2808717 0.5117253 -1.01631154 -0.69491403 0.6960498 0.5381014
## 7 0.2808717 0.9352221 -2.33476975 -0.69491403 0.2749104 -0.7752309
## 8 -1.4043583 -0.3352683 -0.68669699 0.76592714 -1.4096470 -1.4318971
## 9 0.2808717 0.9352221 -1.34592609 -2.15575520 0.6960498 -0.7752309
## 10 -2.2469733 0.9352221 -1.34592609 -0.69491403 -0.9885077 0.5381014
## 11 -2.2469733 0.9352221 -1.34592609 0.76592714 0.2749104 -0.1185647
## 12 0.2808717 0.9352221 -1.01631154 0.40071685 0.6960498 -0.1185647
## 13 0.2808717 0.9352221 0.30214667 0.76592714 0.6960498 -0.7752309
## 14 -0.5617433 -0.3352683 0.96137578 0.40071685 0.6960498 1.8514338
## 15 -6.4600482 0.9352221 1.29099033 -0.69491403 -0.1462289 0.5381014
## 16 0.2808717 0.9352221 -1.34592609 -0.69491403 0.2749104 0.5381014
## 17 0.2808717 0.9352221 -0.68669699 -0.32970374 -3.0942045 0.5381014
## 18 0.2808717 -0.3352683 -1.34592609 -1.06012432 -1.4096470 0.5381014
## 19 0.2808717 -0.7587651 0.30214667 -2.15575520 -1.4096470 0.5381014
## 20 0.2808717 -0.3352683 0.30214667 0.03550656 -1.4096470 0.5381014
## 21 0.2808717 0.9352221 1.29099033 -1.42533462 0.6960498 0.5381014
## 22 0.2808717 -0.3352683 -0.02746788 0.76592714 0.6960498 -0.1185647
## 23 0.2808717 0.0882285 0.96137578 0.76592714 0.6960498 -0.7752309
## 24 0.2808717 0.9352221 0.63176123 0.76592714 0.6960498 -3.4018956
## 25 0.2808717 -0.3352683 -0.35708243 -0.32970374 0.6960498 -0.7752309
## 26 0.2808717 0.9352221 0.63176123 0.76592714 0.6960498 -0.7752309
## 27 0.2808717 0.0882285 1.29099033 0.03550656 -0.1462289 -0.1185647
## 28 0.2808717 0.9352221 -0.02746788 0.76592714 0.6960498 0.5381014
## 29 0.2808717 -0.7587651 -0.02746788 0.76592714 0.2749104 -1.4318971
## 30 0.2808717 0.5117253 -0.35708243 0.40071685 0.6960498 -2.0885632
## 31 0.2808717 -2.0292555 -0.68669699 0.76592714 0.6960498 1.8514338
## 32 0.2808717 0.9352221 1.29099033 0.03550656 -1.8307864 0.5381014
## 33 0.2808717 -1.1822619 -0.02746788 0.76592714 0.6960498 -1.4318971
## 34 0.2808717 -0.7587651 -0.35708243 0.40071685 0.6960498 -1.4318971
## 35 0.2808717 0.9352221 1.29099033 0.76592714 0.6960498 1.8514338
## 36 0.2808717 -4.1467395 -2.00515520 -2.15575520 -1.8307864 -0.7752309
## 37 0.2808717 0.9352221 -0.68669699 -1.79054491 0.6960498 0.5381014
## 38 0.2808717 -1.1822619 0.30214667 -1.06012432 -2.6730651 -0.7752309
## 39 0.2808717 -1.6057587 -0.02746788 0.76592714 0.6960498 -0.1185647
## 40 0.2808717 0.5117253 0.96137578 0.76592714 -0.9885077 -1.4318971
## 41 0.2808717 -0.3352683 -0.02746788 0.76592714 0.6960498 -0.1185647
## 42 0.2808717 0.9352221 0.63176123 0.76592714 0.6960498 -0.7752309
## 43 0.2808717 0.9352221 1.29099033 0.76592714 0.6960498 0.5381014
## 44 0.2808717 0.9352221 1.29099033 0.76592714 0.6960498 1.1947676
## 45 0.2808717 -0.7587651 0.96137578 0.76592714 0.6960498 1.8514338
## 46 0.2808717 0.9352221 0.96137578 0.76592714 -0.9885077 1.8514338
## 47 0.2808717 0.5117253 -0.02746788 0.76592714 0.6960498 1.1947676
## 48 0.2808717 0.9352221 1.29099033 -0.69491403 -0.9885077 -0.1185647
## 49 0.2808717 0.9352221 -0.02746788 0.76592714 0.6960498 0.5381014
## 50 -3.0895883 0.9352221 -0.02746788 0.76592714 -0.5673683 0.5381014
## 51 0.2808717 -0.7587651 1.29099033 0.76592714 -0.9885077 -0.7752309
## 52 0.2808717 0.9352221 1.29099033 0.76592714 0.6960498 1.8514338
## 53 0.2808717 -1.6057587 0.30214667 0.76592714 0.2749104 1.1947676
## 54 0.2808717 0.0882285 0.30214667 -2.15575520 0.6960498 -0.1185647
## 55 0.2808717 0.9352221 1.29099033 0.76592714 -0.9885077 -0.1185647
## 56 0.2808717 -1.6057587 -1.01631154 -2.15575520 0.6960498 -0.7752309
## 57 0.2808717 -1.1822619 -2.00515520 -2.15575520 0.6960498 0.5381014
## 58 0.2808717 -0.7587651 -1.01631154 0.76592714 0.6960498 -0.1185647
## 59 0.2808717 -0.7587651 -0.68669699 -0.69491403 0.6960498 -0.7752309
## 60 0.2808717 0.0882285 -0.68669699 0.76592714 0.6960498 0.5381014
## 61 0.2808717 -0.3352683 -0.35708243 0.76592714 0.6960498 -0.7752309
## 62 0.2808717 -1.1822619 -0.35708243 0.76592714 0.6960498 -0.7752309
## 63 0.2808717 0.0882285 -0.02746788 -0.69491403 0.6960498 0.5381014
## 64 0.2808717 0.0882285 1.29099033 0.76592714 0.6960498 0.5381014
## 65 0.2808717 0.9352221 -1.01631154 -0.69491403 -0.9885077 -0.7752309
## 66 0.2808717 0.0882285 -0.02746788 -0.69491403 0.2749104 1.1947676
## 67 0.2808717 -0.3352683 0.63176123 0.76592714 -0.9885077 -0.1185647
## 68 0.2808717 0.5117253 0.96137578 0.76592714 0.6960498 -0.7752309
## 69 0.2808717 -0.3352683 1.29099033 0.76592714 0.6960498 0.5381014
## 70 0.2808717 -2.0292555 -0.02746788 -0.69491403 -1.4096470 -0.7752309
## 71 -0.5617433 -0.3352683 0.63176123 0.76592714 -0.1462289 -0.7752309
## 72 0.2808717 0.5117253 0.96137578 -0.69491403 -0.5673683 -0.1185647
## X7 X8 X9 X10 X11 X12
## 1 0.9163363 -1.15131090 -0.09905318 -0.3540692 -0.7024641 0.4200606
## 2 -1.0629501 1.01586256 -0.71035282 -1.0557109 -0.9965189 0.7318582
## 3 0.9163363 -1.15131090 -0.91411936 -0.3540692 -0.9965189 -1.7625224
## 4 -1.0629501 -1.15131090 -0.71035282 -1.0557109 -0.9965189 0.7318582
## 5 -0.4031880 -1.15131090 -0.71035282 -1.2895915 -0.9965189 0.7318582
## 6 0.9163363 -1.15131090 -1.11788591 -1.0557109 -0.9965189 0.4200606
## 7 0.9163363 1.01586256 -1.11788591 -0.3540692 -0.9965189 -1.7625224
## 8 0.9163363 1.01586256 -0.71035282 -0.8218304 -0.9965189 -0.8271297
## 9 0.9163363 -1.15131090 -1.11788591 -0.8218304 -0.9965189 -1.1389273
## 10 -0.4031880 1.01586256 -1.11788591 -1.2895915 -0.4084094 0.7318582
## 11 0.2565742 -1.15131090 -1.11788591 -0.1201886 -0.9965189 -2.6979152
## 12 0.9163363 -1.15131090 -1.11788591 -0.3540692 -0.9965189 0.7318582
## 13 0.9163363 -1.15131090 -1.11788591 -1.2895915 -0.9965189 -2.6979152
## 14 0.2565742 -0.06772417 -0.50658627 -1.2895915 -0.9965189 0.7318582
## 15 0.2565742 -1.15131090 -1.11788591 -1.2895915 -0.4084094 0.7318582
## 16 -0.4031880 0.47406920 -0.09905318 0.3475725 -0.9965189 -3.0097128
## 17 -0.4031880 -1.15131090 0.71601300 -0.8218304 -0.4084094 -2.3861176
## 18 -0.4031880 -1.15131090 -0.09905318 0.3475725 -0.4084094 -2.0743200
## 19 -0.4031880 -0.60951754 0.30847991 -0.1201886 0.4737549 -2.0743200
## 20 -1.7227123 -0.60951754 -0.30281973 -0.5879498 -0.9965189 -0.2035345
## 21 0.9163363 1.01586256 -1.11788591 -0.1201886 -0.7024641 -0.5153321
## 22 -0.4031880 -0.06772417 -1.11788591 -1.2895915 -0.9965189 0.1082630
## 23 -0.4031880 -1.15131090 -0.71035282 -0.8218304 -0.9965189 0.7318582
## 24 0.9163363 -1.15131090 -0.71035282 -0.5879498 -0.9965189 0.4200606
## 25 -0.4031880 -0.60951754 -0.91411936 0.1136919 -0.9965189 0.7318582
## 26 0.9163363 -1.15131090 -1.11788591 -0.8218304 -0.9965189 0.7318582
## 27 -0.4031880 -0.06772417 -0.71035282 0.1136919 -0.9965189 0.1082630
## 28 0.9163363 -1.15131090 -1.11788591 -1.2895915 -0.9965189 0.7318582
## 29 -0.4031880 -1.15131090 -0.91411936 -1.2895915 -0.4084094 0.7318582
## 30 -2.3824745 -0.60951754 -0.71035282 -0.3540692 -0.7024641 -0.8271297
## 31 0.9163363 -1.15131090 -1.11788591 -1.2895915 -0.9965189 0.7318582
## 32 0.2565742 0.47406920 -0.30281973 -0.5879498 -0.4084094 -0.2035345
## 33 -0.4031880 -1.15131090 -0.71035282 -1.2895915 0.1797001 0.7318582
## 34 0.9163363 -0.06772417 -1.11788591 -1.2895915 -0.9965189 -0.5153321
## 35 0.9163363 -1.15131090 -1.11788591 -1.2895915 -0.9965189 0.7318582
## 36 0.9163363 -1.15131090 -1.11788591 0.1136919 0.1797001 -0.5153321
## 37 0.9163363 -1.15131090 -1.11788591 -0.8218304 0.1797001 -0.8271297
## 38 -1.7227123 0.47406920 -0.71035282 0.3475725 -0.4084094 -0.5153321
## 39 -1.7227123 -1.15131090 -1.11788591 -0.5879498 -0.9965189 0.7318582
## 40 0.2565742 -1.15131090 -0.71035282 -1.0557109 -0.9965189 0.4200606
## 41 -0.4031880 -0.06772417 -1.11788591 -1.0557109 -0.9965189 0.4200606
## 42 0.9163363 -1.15131090 -0.30281973 -0.3540692 -0.9965189 0.7318582
## 43 -0.4031880 1.01586256 0.51224645 1.5169754 1.3559192 0.7318582
## 44 0.9163363 1.01586256 0.51224645 1.5169754 1.3559192 0.7318582
## 45 0.9163363 1.01586256 1.32731264 1.2830948 1.3559192 0.7318582
## 46 -0.4031880 1.01586256 0.51224645 1.5169754 1.3559192 0.7318582
## 47 0.9163363 1.01586256 1.32731264 1.5169754 1.3559192 0.7318582
## 48 -1.7227123 1.01586256 0.51224645 1.0492142 1.3559192 0.7318582
## 49 0.9163363 -1.15131090 1.32731264 1.5169754 1.3559192 0.7318582
## 50 0.9163363 1.01586256 1.12354609 1.0492142 1.3559192 0.7318582
## 51 0.9163363 1.01586256 1.32731264 0.5814531 1.3559192 0.7318582
## 52 0.9163363 1.01586256 1.32731264 1.2830948 1.0618644 -1.1389273
## 53 -1.7227123 1.01586256 0.51224645 0.5814531 1.0618644 0.7318582
## 54 0.9163363 1.01586256 1.32731264 0.3475725 -0.9965189 0.7318582
## 55 -0.4031880 1.01586256 1.32731264 1.0492142 1.3559192 0.7318582
## 56 0.9163363 -1.15131090 1.32731264 1.5169754 0.7678096 -0.5153321
## 57 0.9163363 1.01586256 0.91977955 1.5169754 1.3559192 0.7318582
## 58 -0.4031880 1.01586256 1.12354609 1.0492142 0.7678096 -0.2035345
## 59 -0.4031880 1.01586256 1.12354609 0.5814531 0.7678096 -0.5153321
## 60 -0.4031880 1.01586256 1.12354609 -0.1201886 0.7678096 -0.5153321
## 61 -0.4031880 1.01586256 1.32731264 0.5814531 0.7678096 0.1082630
## 62 -1.7227123 1.01586256 1.12354609 1.0492142 1.0618644 0.7318582
## 63 0.9163363 1.01586256 1.32731264 -0.3540692 1.3559192 0.1082630
## 64 0.9163363 1.01586256 1.12354609 -0.5879498 0.7678096 0.1082630
## 65 0.9163363 1.01586256 0.51224645 1.5169754 0.7678096 0.7318582
## 66 0.9163363 1.01586256 1.32731264 1.5169754 1.3559192 0.7318582
## 67 -1.0629501 1.01586256 1.12354609 1.5169754 1.0618644 0.4200606
## 68 -1.0629501 1.01586256 1.32731264 1.2830948 1.3559192 0.7318582
## 69 -0.4031880 1.01586256 1.32731264 1.2830948 0.7678096 -0.2035345
## 70 -3.0422366 -0.06772417 0.91977955 0.1136919 0.7678096 0.4200606
## 71 -1.7227123 1.01586256 1.12354609 1.0492142 1.3559192 0.1082630
## 72 -0.4031880 1.01586256 1.32731264 0.8153337 1.3559192 -0.8271297
## X13 X14 X15 X16 X17 X18
## 1 -0.41023682 -0.72993106 0.28762379 0.37646372 0.3339617 0.40186665
## 2 0.80029805 -0.25858544 -0.05752476 -1.24522617 -1.2690545 -1.27202419
## 3 -1.62077169 -1.20127668 -0.05752476 0.14479374 -1.7270592 -1.51115145
## 4 0.80029805 -0.25858544 -0.74782184 -1.47689615 -1.4980569 -1.27202419
## 5 -1.13655774 -1.20127668 -0.05752476 0.37646372 -1.2690545 -1.27202419
## 6 -0.41023682 -0.25858544 -1.43811893 -0.78188620 0.5629640 -0.07638788
## 7 0.80029805 -1.20127668 -1.09297039 1.07147368 -1.7270592 -1.51115145
## 8 -0.16812984 1.15545141 -1.43811893 -0.31854623 -0.5820476 -0.55464240
## 9 1.28451200 1.15545141 1.32306942 1.07147368 0.5629640 1.35837570
## 10 -1.62077169 -0.02291263 -1.43811893 -0.31854623 -1.7270592 -1.27202419
## 11 -1.62077169 -0.25858544 0.97792087 0.60813371 -0.5820476 -1.51115145
## 12 -1.62077169 -1.20127668 -0.05752476 0.60813371 -0.8110499 -1.03289693
## 13 -1.62077169 -1.20127668 -1.43811893 1.07147368 0.5629640 -0.79376966
## 14 1.28451200 -1.20127668 1.32306942 1.07147368 0.1049594 -1.51115145
## 15 -1.62077169 -0.25858544 -0.05752476 -0.78188620 -0.8110499 -0.55464240
## 16 -1.62077169 -1.20127668 -1.43811893 -1.24522617 -1.2690545 -1.03289693
## 17 -1.37866471 -1.20127668 -1.09297039 -1.24522617 -0.8110499 -0.55464240
## 18 -1.62077169 -1.20127668 -1.43811893 -1.47689615 -1.4980569 -1.51115145
## 19 -1.13655774 -1.20127668 -1.43811893 -1.47689615 -1.4980569 -1.27202419
## 20 0.31608410 0.21276017 0.63277233 0.37646372 -0.1240429 0.16273939
## 21 -1.62077169 -1.20127668 -1.43811893 -0.78188620 -0.5820476 -1.03289693
## 22 0.31608410 0.44843298 0.28762379 0.37646372 0.3339617 0.64099391
## 23 0.07397713 0.91977860 0.63277233 1.07147368 1.0209687 1.35837570
## 24 1.04240503 1.39112422 0.63277233 0.83980369 1.0209687 1.11924844
## 25 0.55819108 0.44843298 0.28762379 0.37646372 0.7919664 0.16273939
## 26 0.80029805 0.21276017 0.28762379 0.37646372 1.0209687 0.40186665
## 27 0.31608410 0.91977860 0.97792087 -0.08687624 0.3339617 0.88012117
## 28 0.80029805 1.15545141 1.32306942 1.07147368 1.0209687 0.88012117
## 29 0.31608410 1.15545141 0.97792087 0.60813371 0.5629640 0.64099391
## 30 -0.65234379 -0.96560387 -0.05752476 -0.78188620 -1.2690545 -0.07638788
## 31 0.80029805 0.68410579 -0.05752476 1.07147368 1.0209687 0.16273939
## 32 0.55819108 1.39112422 0.97792087 0.83980369 0.5629640 -0.07638788
## 33 0.80029805 1.15545141 1.32306942 1.07147368 0.5629640 0.88012117
## 34 0.31608410 0.21276017 -0.74782184 -0.31854623 1.0209687 1.35837570
## 35 0.07397713 0.44843298 1.32306942 1.07147368 1.0209687 1.35837570
## 36 0.07397713 0.21276017 0.97792087 0.83980369 -1.0400522 0.16273939
## 37 1.28451200 1.15545141 1.32306942 1.07147368 1.0209687 1.35837570
## 38 -0.16812984 0.68410579 0.63277233 0.14479374 0.1049594 0.16273939
## 39 1.28451200 1.62679702 1.32306942 1.07147368 1.0209687 1.35837570
## 40 1.28451200 0.68410579 0.63277233 0.83980369 0.5629640 0.88012117
## 41 -0.65234379 0.21276017 0.63277233 0.37646372 1.0209687 0.16273939
## 42 -0.65234379 -1.20127668 -0.74782184 -1.70856614 0.1049594 -1.03289693
## 43 1.28451200 1.62679702 1.32306942 1.07147368 1.0209687 1.35837570
## 44 1.28451200 1.62679702 1.32306942 1.07147368 1.0209687 1.35837570
## 45 -0.16812984 0.21276017 -0.74782184 -1.70856614 0.7919664 0.40186665
## 46 1.28451200 1.62679702 1.32306942 1.07147368 1.0209687 1.35837570
## 47 0.80029805 -0.49425825 -0.05752476 0.37646372 1.0209687 0.40186665
## 48 1.28451200 0.68410579 1.32306942 1.07147368 0.1049594 0.40186665
## 49 0.80029805 -1.20127668 -1.43811893 -0.31854623 1.0209687 -0.31551514
## 50 -0.65234379 -0.72993106 -1.43811893 -1.24522617 0.5629640 -0.07638788
## 51 1.28451200 1.62679702 -0.05752476 -0.31854623 1.0209687 1.35837570
## 52 0.80029805 0.91977860 0.97792087 1.07147368 1.0209687 1.35837570
## 53 0.31608410 -1.20127668 -1.43811893 -1.01355618 0.5629640 -0.55464240
## 54 0.55819108 0.68410579 0.28762379 -1.01355618 -0.1240429 -0.07638788
## 55 1.28451200 0.68410579 0.63277233 1.07147368 1.0209687 0.88012117
## 56 0.31608410 1.15545141 1.32306942 1.07147368 0.5629640 0.88012117
## 57 -1.62077169 -1.20127668 -1.43811893 0.60813371 1.0209687 1.35837570
## 58 -0.65234379 -0.96560387 -1.09297039 -1.70856614 -1.4980569 -1.27202419
## 59 -0.65234379 -1.20127668 -1.43811893 -1.70856614 -1.7270592 -1.51115145
## 60 -1.62077169 -1.20127668 -1.43811893 -1.70856614 -1.7270592 -1.51115145
## 61 -0.65234379 -1.20127668 -1.43811893 -1.70856614 -1.7270592 -1.51115145
## 62 -0.16812984 1.15545141 0.63277233 0.83980369 0.5629640 0.64099391
## 63 -0.65234379 -1.20127668 -0.40267330 -1.70856614 -1.7270592 -1.51115145
## 64 -0.65234379 -1.20127668 -0.74782184 -1.70856614 -1.7270592 -0.79376966
## 65 -0.65234379 -1.20127668 -0.74782184 0.14479374 0.5629640 0.16273939
## 66 -1.62077169 -1.20127668 -0.74782184 -0.78188620 -0.8110499 -0.55464240
## 67 0.07397713 -0.49425825 -0.05752476 -1.01355618 -0.3530452 -0.55464240
## 68 0.80029805 0.21276017 0.63277233 0.37646372 0.3339617 0.40186665
## 69 1.04240503 0.68410579 0.28762379 0.60813371 1.0209687 0.40186665
## 70 0.55819108 0.21276017 0.28762379 0.14479374 0.3339617 0.16273939
## 71 0.55819108 0.68410579 0.63277233 0.37646372 0.1049594 0.88012117
## 72 0.80029805 0.68410579 0.97792087 0.83980369 0.5629640 1.35837570
## X19
## 1 -0.50817477
## 2 -1.40057923
## 3 1.05353305
## 4 -1.40057923
## 5 -0.73127588
## 6 -0.95437700
## 7 -1.17747811
## 8 0.38422970
## 9 1.05353305
## 10 -1.40057923
## 11 -0.28507365
## 12 -0.28507365
## 13 0.16112858
## 14 0.16112858
## 15 -1.62368035
## 16 -1.62368035
## 17 -1.62368035
## 18 -1.17747811
## 19 -1.62368035
## 20 -0.28507365
## 21 -1.62368035
## 22 0.38422970
## 23 1.05353305
## 24 1.05353305
## 25 0.83043193
## 26 1.05353305
## 27 0.38422970
## 28 1.05353305
## 29 0.60733082
## 30 0.38422970
## 31 1.05353305
## 32 0.38422970
## 33 0.60733082
## 34 1.05353305
## 35 1.05353305
## 36 -0.06197253
## 37 1.05353305
## 38 0.16112858
## 39 0.83043193
## 40 0.60733082
## 41 0.83043193
## 42 -0.28507365
## 43 1.05353305
## 44 1.05353305
## 45 1.05353305
## 46 1.05353305
## 47 0.83043193
## 48 1.05353305
## 49 0.16112858
## 50 -1.62368035
## 51 -0.28507365
## 52 1.05353305
## 53 -1.62368035
## 54 0.38422970
## 55 0.16112858
## 56 -0.06197253
## 57 1.05353305
## 58 -0.73127588
## 59 -1.62368035
## 60 -1.62368035
## 61 -1.62368035
## 62 0.38422970
## 63 -1.62368035
## 64 -1.62368035
## 65 1.05353305
## 66 0.16112858
## 67 0.16112858
## 68 -0.28507365
## 69 0.83043193
## 70 -0.06197253
## 71 1.05353305
## 72 1.05353305
## attr(,"scaled:center")
## X1 X2 X3 X4 X5 X6 X7 X8
## 9.666667 12.791667 11.083333 7.902778 13.347222 7.180556 8.611111 3.125000
## X9 X10 X11 X12 X13 X14 X15 X16
## 8.486111 8.513889 5.388889 12.652778 9.694444 8.097222 6.166667 10.375000
## X17 X18 X19
## 10.541667 9.319444 10.277778
## attr(,"scaled:scale")
## X1 X2 X3 X4 X5 X6 X7 X8
## 1.186782 2.361293 3.033847 2.738148 2.374511 1.522844 1.515698 1.845722
## X9 X10 X11 X12 X13 X14 X15 X16
## 4.907577 4.275686 3.400727 3.207209 4.130406 4.243171 2.897303 4.316485
## X17 X18 X19
## 4.366768 4.181874 4.482273colSums(is.na(data_pca))## X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19
## 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0#Boxplot
boxplot(data_pca,
main="Boxplot Variabel Penelitian",
col="lightgreen")
# Cek Asumsi Korelasi
mat_corr <- round(cor(data_pca),3)
library(sjPlot);tab_corr(data_pca)| X1 | X2 | X3 | X4 | X5 | X6 | X7 | X8 | X9 | X10 | X11 | X12 | X13 | X14 | X15 | X16 | X17 | X18 | X19 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| X1 | -0.166 | 0.004 | -0.006 | 0.127 | -0.068 | -0.057 | 0.058 | 0.159 | 0.176 | 0.067 | -0.042 | 0.309** | 0.076 | 0.102 | 0.104 | 0.174 | 0.206 | 0.285* | |
| X2 | -0.166 | 0.225 | 0.117 | 0.116 | 0.124 | 0.308** | 0.038 | -0.048 | -0.000 | -0.077 | -0.142 | -0.077 | -0.077 | -0.013 | 0.062 | 0.060 | -0.016 | 0.052 | |
| X3 | 0.004 | 0.225 | 0.442*** | 0.010 | 0.152 | -0.118 | 0.237* | 0.253* | 0.140 | 0.252* | 0.387*** | 0.433*** | 0.389*** | 0.354** | 0.098 | 0.444*** | 0.392*** | 0.199 | |
| X4 | -0.006 | 0.117 | 0.442*** | 0.265* | -0.040 | -0.176 | 0.117 | 0.059 | -0.045 | 0.062 | 0.338** | 0.278* | 0.189 | 0.080 | 0.035 | 0.267* | 0.106 | 0.127 | |
| X5 | 0.127 | 0.116 | 0.010 | 0.265* | -0.006 | 0.230 | 0.012 | -0.032 | -0.012 | -0.022 | 0.181 | 0.104 | 0.001 | 0.016 | 0.016 | 0.146 | 0.057 | 0.176 | |
| X6 | -0.068 | 0.124 | 0.152 | -0.040 | -0.006 | 0.202 | 0.187 | 0.203 | 0.180 | 0.231 | 0.062 | -0.090 | -0.171 | -0.045 | -0.066 | 0.044 | -0.089 | -0.092 | |
| X7 | -0.057 | 0.308** | -0.118 | -0.176 | 0.230 | 0.202 | -0.138 | -0.101 | -0.075 | -0.101 | -0.051 | -0.109 | -0.090 | -0.133 | 0.061 | 0.134 | 0.031 | 0.107 | |
| X8 | 0.058 | 0.038 | 0.237* | 0.117 | 0.012 | 0.187 | -0.138 | 0.643*** | 0.606*** | 0.636*** | 0.145 | 0.055 | -0.038 | -0.215 | -0.248* | -0.103 | -0.049 | -0.123 | |
| X9 | 0.159 | -0.048 | 0.253* | 0.059 | -0.032 | 0.203 | -0.101 | 0.643*** | 0.793*** | 0.854*** | 0.131 | 0.064 | -0.107 | -0.165 | -0.309** | -0.001 | 0.033 | -0.113 | |
| X10 | 0.176 | -0.000 | 0.140 | -0.045 | -0.012 | 0.180 | -0.075 | 0.606*** | 0.793*** | 0.809*** | 0.097 | 0.098 | 0.004 | -0.037 | -0.063 | 0.153 | 0.173 | 0.127 | |
| X11 | 0.067 | -0.077 | 0.252* | 0.062 | -0.022 | 0.231 | -0.101 | 0.636*** | 0.854*** | 0.809*** | 0.220 | 0.135 | 0.019 | -0.047 | -0.110 | 0.115 | 0.186 | 0.007 | |
| X12 | -0.042 | -0.142 | 0.387*** | 0.338** | 0.181 | 0.062 | -0.051 | 0.145 | 0.131 | 0.097 | 0.220 | 0.400*** | 0.282* | 0.250* | 0.116 | 0.391*** | 0.329** | 0.245* | |
| X13 | 0.309** | -0.077 | 0.433*** | 0.278* | 0.104 | -0.090 | -0.109 | 0.055 | 0.064 | 0.098 | 0.135 | 0.400*** | 0.702*** | 0.633*** | 0.513*** | 0.595*** | 0.618*** | 0.523*** | |
| X14 | 0.076 | -0.077 | 0.389*** | 0.189 | 0.001 | -0.171 | -0.090 | -0.038 | -0.107 | 0.004 | 0.019 | 0.282* | 0.702*** | 0.741*** | 0.606*** | 0.634*** | 0.779*** | 0.627*** | |
| X15 | 0.102 | -0.013 | 0.354** | 0.080 | 0.016 | -0.045 | -0.133 | -0.215 | -0.165 | -0.037 | -0.047 | 0.250* | 0.633*** | 0.741*** | 0.737*** | 0.508*** | 0.630*** | 0.646*** | |
| X16 | 0.104 | 0.062 | 0.098 | 0.035 | 0.016 | -0.066 | 0.061 | -0.248* | -0.309** | -0.063 | -0.110 | 0.116 | 0.513*** | 0.606*** | 0.737*** | 0.626*** | 0.631*** | 0.711*** | |
| X17 | 0.174 | 0.060 | 0.444*** | 0.267* | 0.146 | 0.044 | 0.134 | -0.103 | -0.001 | 0.153 | 0.115 | 0.391*** | 0.595*** | 0.634*** | 0.508*** | 0.626*** | 0.836*** | 0.732*** | |
| X18 | 0.206 | -0.016 | 0.392*** | 0.106 | 0.057 | -0.089 | 0.031 | -0.049 | 0.033 | 0.173 | 0.186 | 0.329** | 0.618*** | 0.779*** | 0.630*** | 0.631*** | 0.836*** | 0.744*** | |
| X19 | 0.285* | 0.052 | 0.199 | 0.127 | 0.176 | -0.092 | 0.107 | -0.123 | -0.113 | 0.127 | 0.007 | 0.245* | 0.523*** | 0.627*** | 0.646*** | 0.711*** | 0.732*** | 0.744*** | |
| Computed correlation used pearson-method with listwise-deletion. | |||||||||||||||||||
mat_corr <- round(cor(data_pca),3)
# Cek Asumsi Barlett Test
n = nrow(data_pca)
p = ncol(data_pca)
cortest.bartlett(mat_corr,n=n, diag = TRUE)## $chisq
## [1] 828.6786
##
## $p.value
## [1] 6.848372e-87
##
## $df
## [1] 171# Cek Asumsi KMO
mat_corr <- round(cor(data_pca),3)
KMO(mat_corr)## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = mat_corr)
## Overall MSA = 0.73
## MSA for each item =
## X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16
## 0.44 0.37 0.66 0.56 0.46 0.49 0.45 0.69 0.76 0.76 0.73 0.74 0.86 0.80 0.68 0.74
## X17 X18 X19
## 0.72 0.81 0.87# Menghilangkan Behavior eating
data_pca_step1 <- subset(data_pca, select = -X2)
mat_corr_step1 <- round(cor(data_pca_step1),3)
KMO(mat_corr_step1)## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = mat_corr_step1)
## Overall MSA = 0.74
## MSA for each item =
## X1 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17
## 0.46 0.67 0.56 0.43 0.47 0.41 0.68 0.76 0.78 0.74 0.77 0.86 0.81 0.68 0.74 0.73
## X18 X19
## 0.81 0.87# Menghilangkan Attitude Spontaneity
data_pca_step2 <- subset(data_pca_step1, select = -X7)
mat_corr_step2 <- round(cor(data_pca_step2),3)
KMO(mat_corr_step2)## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = mat_corr_step2)
## Overall MSA = 0.75
## MSA for each item =
## X1 X3 X4 X5 X6 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18
## 0.48 0.67 0.62 0.52 0.49 0.69 0.77 0.78 0.74 0.77 0.86 0.81 0.69 0.75 0.71 0.81
## X19
## 0.88# Menghilangkan Behavior SexualRisk
data_pca_step3 <- subset(data_pca_step2, select = -X1)
mat_corr_step3 <- round(cor(data_pca_step3),3)
KMO(mat_corr_step3)## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = mat_corr_step3)
## Overall MSA = 0.76
## MSA for each item =
## X3 X4 X5 X6 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19
## 0.66 0.61 0.49 0.47 0.69 0.77 0.77 0.75 0.78 0.92 0.83 0.69 0.74 0.71 0.82 0.89# Menghilangkan Attitude Consistency
data_pca_step4 <- subset(data_pca_step3, select = -X6)
mat_corr_step4 <- round(cor(data_pca_step4),3)
KMO(mat_corr_step4)## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = mat_corr_step4)
## Overall MSA = 0.77
## MSA for each item =
## X3 X4 X5 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19
## 0.64 0.63 0.48 0.70 0.77 0.77 0.75 0.78 0.92 0.83 0.70 0.74 0.74 0.83 0.89# Menghilangkan Intention Commitment
data_pca_step5 <- subset(data_pca_step4, select = -X5)
mat_corr_step5 <- round(cor(data_pca_step5),3)
KMO(mat_corr_step5)## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = mat_corr_step5)
## Overall MSA = 0.78
## MSA for each item =
## X3 X4 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19
## 0.66 0.63 0.71 0.77 0.77 0.75 0.76 0.92 0.84 0.70 0.75 0.74 0.83 0.88# Cek Asumsi Korelasi Setelah KMO
mat_corr <- round(cor(data_pca_step5),3)
tab_corr(data_pca_step5)| X3 | X4 | X8 | X9 | X10 | X11 | X12 | X13 | X14 | X15 | X16 | X17 | X18 | X19 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| X3 | 0.442*** | 0.237* | 0.253* | 0.140 | 0.252* | 0.387*** | 0.433*** | 0.389*** | 0.354** | 0.098 | 0.444*** | 0.392*** | 0.199 | |
| X4 | 0.442*** | 0.117 | 0.059 | -0.045 | 0.062 | 0.338** | 0.278* | 0.189 | 0.080 | 0.035 | 0.267* | 0.106 | 0.127 | |
| X8 | 0.237* | 0.117 | 0.643*** | 0.606*** | 0.636*** | 0.145 | 0.055 | -0.038 | -0.215 | -0.248* | -0.103 | -0.049 | -0.123 | |
| X9 | 0.253* | 0.059 | 0.643*** | 0.793*** | 0.854*** | 0.131 | 0.064 | -0.107 | -0.165 | -0.309** | -0.001 | 0.033 | -0.113 | |
| X10 | 0.140 | -0.045 | 0.606*** | 0.793*** | 0.809*** | 0.097 | 0.098 | 0.004 | -0.037 | -0.063 | 0.153 | 0.173 | 0.127 | |
| X11 | 0.252* | 0.062 | 0.636*** | 0.854*** | 0.809*** | 0.220 | 0.135 | 0.019 | -0.047 | -0.110 | 0.115 | 0.186 | 0.007 | |
| X12 | 0.387*** | 0.338** | 0.145 | 0.131 | 0.097 | 0.220 | 0.400*** | 0.282* | 0.250* | 0.116 | 0.391*** | 0.329** | 0.245* | |
| X13 | 0.433*** | 0.278* | 0.055 | 0.064 | 0.098 | 0.135 | 0.400*** | 0.702*** | 0.633*** | 0.513*** | 0.595*** | 0.618*** | 0.523*** | |
| X14 | 0.389*** | 0.189 | -0.038 | -0.107 | 0.004 | 0.019 | 0.282* | 0.702*** | 0.741*** | 0.606*** | 0.634*** | 0.779*** | 0.627*** | |
| X15 | 0.354** | 0.080 | -0.215 | -0.165 | -0.037 | -0.047 | 0.250* | 0.633*** | 0.741*** | 0.737*** | 0.508*** | 0.630*** | 0.646*** | |
| X16 | 0.098 | 0.035 | -0.248* | -0.309** | -0.063 | -0.110 | 0.116 | 0.513*** | 0.606*** | 0.737*** | 0.626*** | 0.631*** | 0.711*** | |
| X17 | 0.444*** | 0.267* | -0.103 | -0.001 | 0.153 | 0.115 | 0.391*** | 0.595*** | 0.634*** | 0.508*** | 0.626*** | 0.836*** | 0.732*** | |
| X18 | 0.392*** | 0.106 | -0.049 | 0.033 | 0.173 | 0.186 | 0.329** | 0.618*** | 0.779*** | 0.630*** | 0.631*** | 0.836*** | 0.744*** | |
| X19 | 0.199 | 0.127 | -0.123 | -0.113 | 0.127 | 0.007 | 0.245* | 0.523*** | 0.627*** | 0.646*** | 0.711*** | 0.732*** | 0.744*** | |
| Computed correlation used pearson-method with listwise-deletion. | ||||||||||||||
mat_corr <- round(cor(data_pca_step5),3)
# Cek Asumsi Barlett Test
n = nrow(data_pca_step5)
p = ncol(data_pca_step5)
cortest.bartlett(mat_corr,n=n, diag = TRUE)## $chisq
## [1] 743.2842
##
## $p.value
## [1] 5.938246e-103
##
## $df
## [1] 91# Matriks korelasi parsial setelah removing
part_corr <- pcor(data_pca_step5)
round(part_corr$estimate, 3)## X3 X4 X8 X9 X10 X11 X12 X13 X14 X15
## X3 1.000 0.293 0.301 0.085 -0.168 0.012 -0.017 -0.011 -0.071 0.449
## X4 0.293 1.000 0.030 0.027 -0.168 0.073 0.148 0.094 0.138 -0.145
## X8 0.301 0.030 1.000 0.100 0.267 0.123 0.139 0.092 0.259 -0.388
## X9 0.085 0.027 0.100 1.000 0.340 0.537 -0.129 0.155 -0.127 0.105
## X10 -0.168 -0.168 0.267 0.340 1.000 0.363 -0.134 -0.069 -0.042 0.093
## X11 0.012 0.073 0.123 0.537 0.363 1.000 0.210 -0.051 -0.050 -0.047
## X12 -0.017 0.148 0.139 -0.129 -0.134 0.210 1.000 0.161 -0.116 0.189
## X13 -0.011 0.094 0.092 0.155 -0.069 -0.051 0.161 1.000 0.288 0.190
## X14 -0.071 0.138 0.259 -0.127 -0.042 -0.050 -0.116 0.288 1.000 0.388
## X15 0.449 -0.145 -0.388 0.105 0.093 -0.047 0.189 0.190 0.388 1.000
## X16 -0.332 0.006 0.182 -0.333 -0.055 0.216 -0.249 0.069 -0.122 0.558
## X17 0.385 0.156 -0.323 0.054 0.220 -0.140 0.230 0.151 -0.007 -0.444
## X18 0.032 -0.285 -0.061 0.003 -0.124 0.252 -0.015 -0.049 0.477 0.018
## X19 -0.231 0.147 0.108 -0.034 0.218 -0.188 0.015 -0.045 -0.073 0.261
## X16 X17 X18 X19
## X3 -0.332 0.385 0.032 -0.231
## X4 0.006 0.156 -0.285 0.147
## X8 0.182 -0.323 -0.061 0.108
## X9 -0.333 0.054 0.003 -0.034
## X10 -0.055 0.220 -0.124 0.218
## X11 0.216 -0.140 0.252 -0.188
## X12 -0.249 0.230 -0.015 0.015
## X13 0.069 0.151 -0.049 -0.045
## X14 -0.122 -0.007 0.477 -0.073
## X15 0.558 -0.444 0.018 0.261
## X16 1.000 0.398 -0.039 0.132
## X17 0.398 1.000 0.514 0.250
## X18 -0.039 0.514 1.000 0.247
## X19 0.132 0.250 0.247 1.000# eigen value
pca <- prcomp(data_pca_step5, scale = TRUE)
library(factoextra)
eig.val <- get_eigenvalue(pca)
eig.val## eigenvalue variance.percent cumulative.variance.percent
## Dim.1 5.38806298 38.4861641 38.48616
## Dim.2 3.43077726 24.5055519 62.99172
## Dim.3 1.45533301 10.3952358 73.38695
## Dim.4 0.69699433 4.9785309 78.36548
## Dim.5 0.64967405 4.6405290 83.00601
## Dim.6 0.54906851 3.9219179 86.92793
## Dim.7 0.43233622 3.0881159 90.01605
## Dim.8 0.39297603 2.8069717 92.82302
## Dim.9 0.29505520 2.1075371 94.93055
## Dim.10 0.25979103 1.8556502 96.78620
## Dim.11 0.16467470 1.1762479 97.96245
## Dim.12 0.11437049 0.8169321 98.77938
## Dim.13 0.09693172 0.6923695 99.47175
## Dim.14 0.07395447 0.5282462 100.00000# Scree Plot
fviz_eig(prcomp(data_pca_step5, scale=TRUE),
addlabels=TRUE)## Warning in geom_bar(stat = "identity", fill = barfill, color = barcolor, :
## Ignoring empty aesthetic: `width`.
# Jalankan PCA
pca_psych <- principal(data_pca_step5,
nfactors = 3,
rotate = "none")
print(pca_psych, digits = 3)## Principal Components Analysis
## Call: principal(r = data_pca_step5, nfactors = 3, rotate = "none")
## Standardized loadings (pattern matrix) based upon correlation matrix
## PC1 PC2 PC3 h2 u2 com
## X3 0.518 0.336 0.516 0.648 0.352 2.69
## X4 0.292 0.150 0.751 0.671 0.329 1.39
## X8 -0.047 0.809 0.026 0.657 0.343 1.01
## X9 -0.018 0.928 -0.115 0.875 0.125 1.03
## X10 0.128 0.844 -0.372 0.867 0.133 1.43
## X11 0.132 0.905 -0.185 0.871 0.129 1.13
## X12 0.458 0.247 0.470 0.492 0.508 2.50
## X13 0.798 0.077 0.116 0.656 0.344 1.06
## X14 0.856 -0.095 -0.029 0.743 0.257 1.03
## X15 0.808 -0.216 -0.122 0.714 0.286 1.19
## X16 0.755 -0.332 -0.305 0.773 0.227 1.73
## X17 0.859 0.016 -0.007 0.738 0.262 1.00
## X18 0.890 0.034 -0.177 0.824 0.176 1.08
## X19 0.816 -0.125 -0.253 0.745 0.255 1.24
##
## PC1 PC2 PC3
## SS loadings 5.388 3.431 1.455
## Proportion Var 0.385 0.245 0.104
## Cumulative Var 0.385 0.630 0.734
## Proportion Explained 0.524 0.334 0.142
## Cumulative Proportion 0.524 0.858 1.000
##
## Mean item complexity = 1.4
## Test of the hypothesis that 3 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0.041
## with the empirical chi square 22.334 with prob < 1
##
## Fit based upon off diagonal values = 0.99# Jalankan FA
fa_final <- principal(data_pca_step5,
nfactors = 3,
rotate = "varimax")
print(fa_final, digits = 3)## Principal Components Analysis
## Call: principal(r = data_pca_step5, nfactors = 3, rotate = "varimax")
## Standardized loadings (pattern matrix) based upon correlation matrix
## RC1 RC2 RC3 h2 u2 com
## X3 0.271 0.208 0.729 0.648 0.352 1.45
## X4 0.011 -0.046 0.818 0.671 0.329 1.01
## X8 -0.168 0.767 0.201 0.657 0.343 1.24
## X9 -0.113 0.922 0.112 0.875 0.125 1.06
## X10 0.119 0.919 -0.090 0.867 0.133 1.05
## X11 0.054 0.927 0.096 0.871 0.129 1.03
## X12 0.242 0.132 0.645 0.492 0.508 1.37
## X13 0.699 0.084 0.401 0.656 0.344 1.63
## X14 0.825 -0.038 0.249 0.743 0.257 1.18
## X15 0.826 -0.132 0.119 0.714 0.286 1.09
## X16 0.852 -0.196 -0.094 0.773 0.227 1.13
## X17 0.804 0.062 0.297 0.738 0.262 1.28
## X18 0.885 0.128 0.157 0.824 0.176 1.11
## X19 0.863 -0.008 0.025 0.745 0.255 1.00
##
## RC1 RC2 RC3
## SS loadings 4.942 3.287 2.045
## Proportion Var 0.353 0.235 0.146
## Cumulative Var 0.353 0.588 0.734
## Proportion Explained 0.481 0.320 0.199
## Cumulative Proportion 0.481 0.801 1.000
##
## Mean item complexity = 1.2
## Test of the hypothesis that 3 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0.041
## with the empirical chi square 22.334 with prob < 1
##
## Fit based upon off diagonal values = 0.99