minggu 7
dataA <- read.csv("df_mahasiswa.csv")
dataA## X id_mahasiswa jenis_kelamin jam_belajar_per_hari frekuensi_login_lms
## 1 1 MHS001 L 4 1
## 2 2 MHS002 P 4 2
## 3 3 MHS003 P 2 6
## 4 4 MHS004 P 5 3
## 5 5 MHS005 L 3 2
## 6 6 MHS006 L 3 7
## 7 7 MHS007 P 1 7
## 8 8 MHS008 L 3 4
## 9 9 MHS009 P 2 6
## 10 10 MHS010 L 1 5
## 11 11 MHS011 L 1 1
## 12 12 MHS012 P 1 2
## 13 13 MHS013 P 2 6
## 14 14 MHS014 L 4 2
## 15 15 MHS015 L 1 2
## 16 16 MHS016 L 5 1
## 17 17 MHS017 L 2 7
## 18 18 MHS018 L 5 7
## 19 19 MHS019 L 5 2
## 20 20 MHS020 L 3 1
## 21 21 MHS021 L 1 6
## 22 22 MHS022 P 4 7
## 23 23 MHS023 L 4 4
## 24 24 MHS024 P 5 4
## 25 25 MHS025 L 3 1
## 26 26 MHS026 L 4 6
## 27 27 MHS027 L 2 3
## 28 28 MHS028 P 2 6
## 29 29 MHS029 L 2 2
## 30 30 MHS030 P 5 3
## 31 31 MHS031 P 2 7
## 32 32 MHS032 L 1 2
## 33 33 MHS033 P 1 7
## 34 34 MHS034 P 5 4
## 35 35 MHS035 L 4 1
## 36 36 MHS036 P 3 1
## 37 37 MHS037 L 4 6
## 38 38 MHS038 L 4 1
## 39 39 MHS039 P 1 1
## 40 40 MHS040 L 4 2
## 41 41 MHS041 L 5 7
## 42 42 MHS042 P 4 6
## 43 43 MHS043 P 4 5
## 44 44 MHS044 P 2 7
## 45 45 MHS045 P 5 2
## 46 46 MHS046 L 1 3
## 47 47 MHS047 L 4 5
## 48 48 MHS048 L 5 4
## 49 49 MHS049 P 4 5
## 50 50 MHS050 P 2 4
## 51 51 MHS051 L 4 6
## 52 52 MHS052 L 4 4
## 53 53 MHS053 L 3 4
## 54 54 MHS054 L 5 4
## 55 55 MHS055 P 2 7
## motivasi_belajar ipk
## 1 82 3.12
## 2 73 3.45
## 3 71 3.07
## 4 98 3.43
## 5 81 2.83
## 6 61 3.10
## 7 44 2.98
## 8 69 3.08
## 9 44 2.82
## 10 46 2.93
## 11 56 2.64
## 12 35 2.71
## 13 59 3.11
## 14 81 3.31
## 15 44 2.90
## 16 90 3.46
## 17 52 3.06
## 18 92 3.89
## 19 84 3.09
## 20 73 2.73
## 21 47 2.96
## 22 72 3.69
## 23 83 3.54
## 24 81 3.61
## 25 70 2.65
## 26 89 3.32
## 27 59 2.94
## 28 53 3.14
## 29 48 2.89
## 30 87 3.40
## 31 71 3.22
## 32 39 2.66
## 33 46 3.11
## 34 87 3.56
## 35 91 3.13
## 36 66 2.95
## 37 68 3.67
## 38 90 3.29
## 39 52 2.52
## 40 80 3.17
## 41 90 3.73
## 42 73 3.05
## 43 91 3.29
## 44 63 3.15
## 45 96 3.33
## 46 43 2.49
## 47 82 3.13
## 48 92 3.70
## 49 73 3.22
## 50 57 3.05
## 51 92 3.65
## 52 88 3.30
## 53 80 3.29
## 54 100 3.41
## 55 71 3.21head(dataA)## X id_mahasiswa jenis_kelamin jam_belajar_per_hari frekuensi_login_lms
## 1 1 MHS001 L 4 1
## 2 2 MHS002 P 4 2
## 3 3 MHS003 P 2 6
## 4 4 MHS004 P 5 3
## 5 5 MHS005 L 3 2
## 6 6 MHS006 L 3 7
## motivasi_belajar ipk
## 1 82 3.12
## 2 73 3.45
## 3 71 3.07
## 4 98 3.43
## 5 81 2.83
## 6 61 3.10str(dataA)## 'data.frame': 55 obs. of 7 variables:
## $ X : int 1 2 3 4 5 6 7 8 9 10 ...
## $ id_mahasiswa : chr "MHS001" "MHS002" "MHS003" "MHS004" ...
## $ jenis_kelamin : chr "L" "P" "P" "P" ...
## $ jam_belajar_per_hari: int 4 4 2 5 3 3 1 3 2 1 ...
## $ frekuensi_login_lms : int 1 2 6 3 2 7 7 4 6 5 ...
## $ motivasi_belajar : int 82 73 71 98 81 61 44 69 44 46 ...
## $ ipk : num 3.12 3.45 3.07 3.43 2.83 3.1 2.98 3.08 2.82 2.93 ...colSums(is.na(dataA))## X id_mahasiswa jenis_kelamin
## 0 0 0
## jam_belajar_per_hari frekuensi_login_lms motivasi_belajar
## 0 0 0
## ipk
## 0table(dataA$jenis_kelamin)##
## L P
## 32 23unique(dataA$id_mahasiswa)## [1] "MHS001" "MHS002" "MHS003" "MHS004" "MHS005" "MHS006" "MHS007" "MHS008"
## [9] "MHS009" "MHS010" "MHS011" "MHS012" "MHS013" "MHS014" "MHS015" "MHS016"
## [17] "MHS017" "MHS018" "MHS019" "MHS020" "MHS021" "MHS022" "MHS023" "MHS024"
## [25] "MHS025" "MHS026" "MHS027" "MHS028" "MHS029" "MHS030" "MHS031" "MHS032"
## [33] "MHS033" "MHS034" "MHS035" "MHS036" "MHS037" "MHS038" "MHS039" "MHS040"
## [41] "MHS041" "MHS042" "MHS043" "MHS044" "MHS045" "MHS046" "MHS047" "MHS048"
## [49] "MHS049" "MHS050" "MHS051" "MHS052" "MHS053" "MHS054" "MHS055"length(dataA$id_mahasiswa)## [1] 55library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, uniondataA %>%
filter(jam_belajar_per_hari > 4) %>%
group_by(id_mahasiswa) %>%
summarise(jam_belajar_per_hari) %>%
arrange(desc(jam_belajar_per_hari)) %>%
head(10)## # A tibble: 10 × 2
## id_mahasiswa jam_belajar_per_hari
## <chr> <int>
## 1 MHS004 5
## 2 MHS016 5
## 3 MHS018 5
## 4 MHS019 5
## 5 MHS024 5
## 6 MHS030 5
## 7 MHS034 5
## 8 MHS041 5
## 9 MHS045 5
## 10 MHS048 5dataA %>%
filter(frekuensi_login_lms > 6) %>%
group_by(id_mahasiswa) %>%
summarise(frekuensi_login_lms) %>%
arrange(desc(frekuensi_login_lms)) %>%
head(10)## # A tibble: 10 × 2
## id_mahasiswa frekuensi_login_lms
## <chr> <int>
## 1 MHS006 7
## 2 MHS007 7
## 3 MHS017 7
## 4 MHS018 7
## 5 MHS022 7
## 6 MHS031 7
## 7 MHS033 7
## 8 MHS041 7
## 9 MHS044 7
## 10 MHS055 7dataA %>%
filter(motivasi_belajar > 90) %>%
group_by(id_mahasiswa) %>%
summarise(motivasi_belajar) %>%
arrange(desc(motivasi_belajar)) %>%
head(10)## # A tibble: 8 × 2
## id_mahasiswa motivasi_belajar
## <chr> <int>
## 1 MHS054 100
## 2 MHS004 98
## 3 MHS045 96
## 4 MHS018 92
## 5 MHS048 92
## 6 MHS051 92
## 7 MHS035 91
## 8 MHS043 91dataA %>%
filter(ipk > 3) %>%
group_by(id_mahasiswa) %>%
summarise(ipk) %>%
arrange(desc(ipk)) %>%
head(10)## # A tibble: 10 × 2
## id_mahasiswa ipk
## <chr> <dbl>
## 1 MHS018 3.89
## 2 MHS041 3.73
## 3 MHS048 3.7
## 4 MHS022 3.69
## 5 MHS037 3.67
## 6 MHS051 3.65
## 7 MHS024 3.61
## 8 MHS034 3.56
## 9 MHS023 3.54
## 10 MHS016 3.46dataf <- subset(dataA, jam_belajar_per_hari >= 4 )
dataf## X id_mahasiswa jenis_kelamin jam_belajar_per_hari frekuensi_login_lms
## 1 1 MHS001 L 4 1
## 2 2 MHS002 P 4 2
## 4 4 MHS004 P 5 3
## 14 14 MHS014 L 4 2
## 16 16 MHS016 L 5 1
## 18 18 MHS018 L 5 7
## 19 19 MHS019 L 5 2
## 22 22 MHS022 P 4 7
## 23 23 MHS023 L 4 4
## 24 24 MHS024 P 5 4
## 26 26 MHS026 L 4 6
## 30 30 MHS030 P 5 3
## 34 34 MHS034 P 5 4
## 35 35 MHS035 L 4 1
## 37 37 MHS037 L 4 6
## 38 38 MHS038 L 4 1
## 40 40 MHS040 L 4 2
## 41 41 MHS041 L 5 7
## 42 42 MHS042 P 4 6
## 43 43 MHS043 P 4 5
## 45 45 MHS045 P 5 2
## 47 47 MHS047 L 4 5
## 48 48 MHS048 L 5 4
## 49 49 MHS049 P 4 5
## 51 51 MHS051 L 4 6
## 52 52 MHS052 L 4 4
## 54 54 MHS054 L 5 4
## motivasi_belajar ipk
## 1 82 3.12
## 2 73 3.45
## 4 98 3.43
## 14 81 3.31
## 16 90 3.46
## 18 92 3.89
## 19 84 3.09
## 22 72 3.69
## 23 83 3.54
## 24 81 3.61
## 26 89 3.32
## 30 87 3.40
## 34 87 3.56
## 35 91 3.13
## 37 68 3.67
## 38 90 3.29
## 40 80 3.17
## 41 90 3.73
## 42 73 3.05
## 43 91 3.29
## 45 96 3.33
## 47 82 3.13
## 48 92 3.70
## 49 73 3.22
## 51 92 3.65
## 52 88 3.30
## 54 100 3.41df <- subset(dataA, frekuensi_login_lms > 5)
df## X id_mahasiswa jenis_kelamin jam_belajar_per_hari frekuensi_login_lms
## 3 3 MHS003 P 2 6
## 6 6 MHS006 L 3 7
## 7 7 MHS007 P 1 7
## 9 9 MHS009 P 2 6
## 13 13 MHS013 P 2 6
## 17 17 MHS017 L 2 7
## 18 18 MHS018 L 5 7
## 21 21 MHS021 L 1 6
## 22 22 MHS022 P 4 7
## 26 26 MHS026 L 4 6
## 28 28 MHS028 P 2 6
## 31 31 MHS031 P 2 7
## 33 33 MHS033 P 1 7
## 37 37 MHS037 L 4 6
## 41 41 MHS041 L 5 7
## 42 42 MHS042 P 4 6
## 44 44 MHS044 P 2 7
## 51 51 MHS051 L 4 6
## 55 55 MHS055 P 2 7
## motivasi_belajar ipk
## 3 71 3.07
## 6 61 3.10
## 7 44 2.98
## 9 44 2.82
## 13 59 3.11
## 17 52 3.06
## 18 92 3.89
## 21 47 2.96
## 22 72 3.69
## 26 89 3.32
## 28 53 3.14
## 31 71 3.22
## 33 46 3.11
## 37 68 3.67
## 41 90 3.73
## 42 73 3.05
## 44 63 3.15
## 51 92 3.65
## 55 71 3.21data_filter <- subset(dataA, ipk > 3.5 & motivasi_belajar > 85)
data_filter## X id_mahasiswa jenis_kelamin jam_belajar_per_hari frekuensi_login_lms
## 18 18 MHS018 L 5 7
## 34 34 MHS034 P 5 4
## 41 41 MHS041 L 5 7
## 48 48 MHS048 L 5 4
## 51 51 MHS051 L 4 6
## motivasi_belajar ipk
## 18 92 3.89
## 34 87 3.56
## 41 90 3.73
## 48 92 3.70
## 51 92 3.65mean(dataA$jam_belajar_per_hari)## [1] 3.127273aggregate(jam_belajar_per_hari ~ jenis_kelamin, data = dataA, mean)## jenis_kelamin jam_belajar_per_hari
## 1 L 3.250000
## 2 P 2.956522mean(dataA$ipk)## [1] 3.166aggregate(ipk ~ jenis_kelamin, data = dataA, mean)## jenis_kelamin ipk
## 1 L 3.158125
## 2 P 3.176957aggregate( motivasi_belajar ~ jenis_kelamin, data = dataA, mean)## jenis_kelamin motivasi_belajar
## 1 L 73.18750
## 2 P 67.95652library(ggplot2)
ggplot(dataA,aes(x = id_mahasiswa, y = jam_belajar_per_hari)) + geom_bar(stat = "identity", fill = "blue") + labs(title = "Grafik jam belajar mahasiswa", x = "ID Mahasiswa", y = "Jam Belajar per Hari")