Data Hasil UN SMP Kota Bandung 2015

  1. un-smp-bandung-2015.ods
  2. un-smp-bandung-2015.xlsx
  3. un-smp-bandung-2015.csv

Sumber: http://disdikkota.bandung.go.id/webtemp/index.php/informasi/111-statisik-capaian-nun-smp-kota-bandung-2015?tmpl=component&print=1&page=

Requirements

install.packages('dplyr')
install.packages('ggplot2')
install.packages('scales')

Analysis

Data source: http://disdikkota.bandung.go.id/webtemp/index.php/informasi/111-statisik-capaian-nun-smp-kota-bandung-2015?tmpl=component&print=1&page=

library(dplyr)
library(plyr)
library(pander)
library(ggplot2)
library(scales)
#library(xlsx)
#un_smp <- read.xlsx2('un-smp-bandung-2015.xlsx', 0)
un_smp <- read.csv('un-smp-bandung-2015.csv', header = TRUE, stringsAsFactors = FALSE)
#typeof(un_smp$score)
un_smp <- subset(un_smp, !(un_smp$score %in% c('< 15')))
un_smp$score <- as.double(un_smp$score)
#typeof(un_smp$score)
#un_smp$score <- sapply(un_smp$score, as.numeric)
#data.frame(un_smp, score = as.double(un_smp$score), freq = un_smp$freq,
#           typ=typeof(un_smp$score))
#un_smp[rep()]

studentCount <- sum(un_smp$freq)
un_smp_one <- data.frame(score=floor(un_smp$score), freq=un_smp$freq)
un_smp_one <- ddply(un_smp_one, ~score, summarise, freq=sum(freq))
un_smp_one <- un_smp_one %>% arrange(-row_number(score))
un_smp$cumFreq <- cumsum(un_smp$freq)
un_smp$topPercent <- percent(un_smp$cumFreq / studentCount)
un_smp_one$cumFreq <- cumsum(un_smp_one$freq)
un_smp_one$topPercent <- percent(un_smp_one$cumFreq / studentCount)

un_factor <- c()
un_factor_one <- c()
for (rn in rownames(un_smp)) {
  #print(typeof(un_smp[rn, 'score']))
  un_factor <- c(un_factor, rep(un_smp[rn, 'score'], un_smp[rn, 'freq']))
  un_factor_one <- c(un_factor_one, rep(floor(un_smp[rn, 'score']), un_smp[rn, 'freq']))
  #count(un_factor)
  #un_smp[rn, 'topPercent'] <- un_smp[rn, 'cumFreq'] / count(un_factor)
}
un_factor <- data.frame(score = un_factor)
un_factor_one <- data.frame(score = un_factor_one)

pander(summary(un_factor))
score
Min. :15.00
1st Qu.:20.35
Median :24.40
Mean :25.07
3rd Qu.:29.25
Max. :39.50 
#qplot(un_factor, geom='histogram')
ggplot(data=un_factor, aes(x=score)) + 
  scale_x_continuous(breaks=seq(15, 40, by=1)) +
  geom_histogram(breaks=seq(15, 40, by=1), color="#000020", fill="darkblue") + 
  #geom_density(color="#ff6666") +
  geom_vline(aes(xintercept=mean(score, na.rm=T)),   # Ignore NA values for mean
               color="red", linetype="dashed", size=1)

  ggtitle('Distribusi nilai UN SMP Bandung 2015')
## $title
## [1] "Distribusi nilai UN SMP Bandung 2015"
## 
## attr(,"class")
## [1] "labels"
#hist(un_factor)

pander(un_smp_one, caption = 'Distribusi sederhana nilai UN SMP Bandung 2015 (plus kumulatif)')
Distribusi sederhana nilai UN SMP Bandung 2015 (plus kumulatif)
score freq cumFreq topPercent
39 17 17 0.0%
38 236 253 0.6%
37 667 920 2.3%
36 884 1804 4.6%
35 925 2729 6.9%
34 1093 3822 9.7%
33 1119 4941 12.5%
32 1156 6097 15.5%
31 1220 7317 18.6%
30 1399 8716 22.1%
29 1598 10314 26.2%
28 1800 12114 30.7%
27 2011 14125 35.8%
26 2206 16331 41.4%
25 2177 18508 46.9%
24 2256 20764 52.7%
23 2300 23064 58.5%
22 2479 25543 64.8%
21 2531 28074 71.2%
20 2340 30414 77.1%
19 2250 32664 82.8%
18 2169 34833 88.3%
17 1901 36734 93.2%
16 1572 38306 97.2%
15 1121 39427 100.0% 
pander(un_smp, caption = 'Distribusi detail nilai UN SMP Bandung 2015 (plus kumulatif)')
Distribusi detail nilai UN SMP Bandung 2015 (plus kumulatif)
score freq cumFreq topPercent
39.5 1 1 0.0%
39.4 1 2 0.0%
39.35 2 4 0.0%
39.25 1 5 0.0%
39.15 3 8 0.0%
39.1 4 12 0.0%
39 5 17 0.0%
38.95 5 22 0.1%
38.9 5 27 0.1%
38.85 4 31 0.1%
38.8 5 36 0.1%
38.75 5 41 0.1%
38.7 8 49 0.1%
38.65 3 52 0.1%
38.6 4 56 0.1%
38.55 13 69 0.2%
38.5 16 85 0.2%
38.45 12 97 0.2%
38.4 11 108 0.3%
38.35 14 122 0.3%
38.3 21 143 0.4%
38.25 25 168 0.4%
38.2 13 181 0.5%
38.15 15 196 0.5%
38.1 12 208 0.5%
38.05 25 233 0.6%
38 20 253 0.6%
37.95 20 273 0.7%
37.9 14 287 0.7%
37.85 24 311 0.8%
37.8 28 339 0.9%
37.75 25 364 0.9%
37.7 22 386 1.0%
37.65 24 410 1.0%
37.6 32 442 1.1%
37.55 37 479 1.2%
37.5 39 518 1.3%
37.45 38 556 1.4%
37.4 30 586 1.5%
37.35 53 639 1.6%
37.3 44 683 1.7%
37.25 35 718 1.8%
37.2 27 745 1.9%
37.15 37 782 2.0%
37.1 49 831 2.1%
37.05 45 876 2.2%
37 44 920 2.3%
36.95 57 977 2.5%
36.9 42 1019 2.6%
36.85 42 1061 2.7%
36.8 41 1102 2.8%
36.75 31 1133 2.9%
36.7 39 1172 3.0%
36.65 38 1210 3.1%
36.6 36 1246 3.2%
36.55 45 1291 3.3%
36.5 49 1340 3.4%
36.45 30 1370 3.5%
36.4 45 1415 3.6%
36.35 43 1458 3.7%
36.3 54 1512 3.8%
36.25 48 1560 4.0%
36.2 49 1609 4.1%
36.15 48 1657 4.2%
36.1 49 1706 4.3%
36.05 49 1755 4.5%
36 49 1804 4.6%
35.95 43 1847 4.7%
35.9 46 1893 4.8%
35.85 43 1936 4.9%
35.8 59 1995 5.1%
35.75 48 2043 5.2%
35.7 39 2082 5.3%
35.65 46 2128 5.4%
35.6 41 2169 5.5%
35.55 43 2212 5.6%
35.5 40 2252 5.7%
35.45 46 2298 5.8%
35.4 52 2350 6.0%
35.35 50 2400 6.1%
35.3 52 2452 6.2%
35.25 49 2501 6.3%
35.2 52 2553 6.5%
35.15 37 2590 6.6%
35.1 47 2637 6.7%
35.05 52 2689 6.8%
35 40 2729 6.9%
34.95 48 2777 7.0%
34.9 44 2821 7.2%
34.85 48 2869 7.3%
34.8 57 2926 7.4%
34.75 54 2980 7.6%
34.7 50 3030 7.7%
34.65 45 3075 7.8%
34.6 52 3127 7.9%
34.55 43 3170 8.0%
34.5 64 3234 8.2%
34.45 52 3286 8.3%
34.4 66 3352 8.5%
34.35 69 3421 8.7%
34.3 56 3477 8.8%
34.25 50 3527 8.9%
34.2 60 3587 9.1%
34.15 55 3642 9.2%
34.1 59 3701 9.4%
34.05 60 3761 9.5%
34 61 3822 9.7%
33.95 55 3877 9.8%
33.9 48 3925 10.0%
33.85 58 3983 10.1%
33.8 60 4043 10.3%
33.75 58 4101 10.4%
33.7 61 4162 10.6%
33.65 56 4218 10.7%
33.6 62 4280 10.9%
33.55 59 4339 11.0%
33.5 48 4387 11.1%
33.45 55 4442 11.3%
33.4 52 4494 11.4%
33.35 65 4559 11.6%
33.3 52 4611 11.7%
33.25 65 4676 11.9%
33.2 58 4734 12.0%
33.15 50 4784 12.1%
33.1 54 4838 12.3%
33.05 44 4882 12.4%
33 59 4941 12.5%
32.95 61 5002 12.7%
32.9 67 5069 12.9%
32.85 58 5127 13.0%
32.8 53 5180 13.1%
32.75 41 5221 13.2%
32.7 59 5280 13.4%
32.65 62 5342 13.5%
32.6 71 5413 13.7%
32.55 58 5471 13.9%
32.5 56 5527 14.0%
32.45 54 5581 14.2%
32.4 58 5639 14.3%
32.35 48 5687 14.4%
32.3 54 5741 14.6%
32.25 56 5797 14.7%
32.2 69 5866 14.9%
32.15 62 5928 15.0%
32.1 55 5983 15.2%
32.05 58 6041 15.3%
32 56 6097 15.5%
31.95 60 6157 15.6%
31.9 57 6214 15.8%
31.85 63 6277 15.9%
31.8 57 6334 16.1%
31.75 66 6400 16.2%
31.7 54 6454 16.4%
31.65 72 6526 16.6%
31.6 73 6599 16.7%
31.55 57 6656 16.9%
31.5 65 6721 17.0%
31.45 62 6783 17.2%
31.4 69 6852 17.4%
31.35 61 6913 17.5%
31.3 59 6972 17.7%
31.25 54 7026 17.8%
31.2 53 7079 18.0%
31.15 63 7142 18.1%
31.1 52 7194 18.2%
31.05 62 7256 18.4%
31 61 7317 18.6%
30.95 67 7384 18.7%
30.9 59 7443 18.9%
30.85 61 7504 19.0%
30.8 79 7583 19.2%
30.75 75 7658 19.4%
30.7 64 7722 19.6%
30.65 65 7787 19.8%
30.6 66 7853 19.9%
30.55 60 7913 20.1%
30.5 69 7982 20.2%
30.45 71 8053 20.4%
30.4 80 8133 20.6%
30.35 74 8207 20.8%
30.3 65 8272 21.0%
30.25 68 8340 21.2%
30.2 64 8404 21.3%
30.15 74 8478 21.5%
30.1 71 8549 21.7%
30.05 80 8629 21.9%
30 87 8716 22.1%
29.95 68 8784 22.3%
29.9 60 8844 22.4%
29.85 75 8919 22.6%
29.8 85 9004 22.8%
29.75 92 9096 23.1%
29.7 79 9175 23.3%
29.65 84 9259 23.5%
29.6 89 9348 23.7%
29.55 72 9420 23.9%
29.5 70 9490 24.1%
29.45 83 9573 24.3%
29.4 72 9645 24.5%
29.35 91 9736 24.7%
29.3 74 9810 24.9%
29.25 91 9901 25.1%
29.2 83 9984 25.3%
29.15 85 10069 25.5%
29.1 71 10140 25.7%
29.05 83 10223 25.9%
29 91 10314 26.2%
28.95 104 10418 26.4%
28.9 86 10504 26.6%
28.85 97 10601 26.9%
28.8 77 10678 27.1%
28.75 100 10778 27.3%
28.7 73 10851 27.5%
28.65 83 10934 27.7%
28.6 99 11033 28.0%
28.55 91 11124 28.2%
28.5 93 11217 28.5%
28.45 78 11295 28.6%
28.4 84 11379 28.9%
28.35 89 11468 29.1%
28.3 99 11567 29.3%
28.25 90 11657 29.6%
28.2 80 11737 29.8%
28.15 106 11843 30.0%
28.1 73 11916 30.2%
28.05 98 12014 30.5%
28 100 12114 30.7%
27.95 100 12214 31.0%
27.9 97 12311 31.2%
27.85 100 12411 31.5%
27.8 75 12486 31.7%
27.75 98 12584 31.9%
27.7 97 12681 32.2%
27.65 98 12779 32.4%
27.6 89 12868 32.6%
27.55 78 12946 32.8%
27.5 92 13038 33.1%
27.45 105 13143 33.3%
27.4 103 13246 33.6%
27.35 111 13357 33.9%
27.3 94 13451 34.1%
27.25 113 13564 34.4%
27.2 95 13659 34.6%
27.15 116 13775 34.9%
27.1 130 13905 35.3%
27.05 117 14022 35.6%
27 103 14125 35.8%
26.95 108 14233 36.1%
26.9 99 14332 36.4%
26.85 92 14424 36.6%
26.8 104 14528 36.8%
26.75 111 14639 37.1%
26.7 130 14769 37.5%
26.65 119 14888 37.8%
26.6 98 14986 38.0%
26.55 107 15093 38.3%
26.5 130 15223 38.6%
26.45 110 15333 38.9%
26.4 119 15452 39.2%
26.35 103 15555 39.5%
26.3 120 15675 39.8%
26.25 102 15777 40.0%
26.2 105 15882 40.3%
26.15 129 16011 40.6%
26.1 106 16117 40.9%
26.05 102 16219 41.1%
26 112 16331 41.4%
25.95 110 16441 41.7%
25.9 124 16565 42.0%
25.85 101 16666 42.3%
25.8 96 16762 42.5%
25.75 107 16869 42.8%
25.7 124 16993 43.1%
25.65 106 17099 43.4%
25.6 124 17223 43.7%
25.55 95 17318 43.9%
25.5 118 17436 44.2%
25.45 125 17561 44.5%
25.4 115 17676 44.8%
25.35 117 17793 45.1%
25.3 104 17897 45.4%
25.25 96 17993 45.6%
25.2 107 18100 45.9%
25.15 92 18192 46.1%
25.1 116 18308 46.4%
25.05 104 18412 46.7%
25 96 18508 46.9%
24.95 102 18610 47.2%
24.9 123 18733 47.5%
24.85 95 18828 47.8%
24.8 95 18923 48.0%
24.75 135 19058 48.3%
24.7 104 19162 48.6%
24.65 121 19283 48.9%
24.6 115 19398 49.2%
24.55 104 19502 49.5%
24.5 106 19608 49.7%
24.45 105 19713 50.0%
24.4 134 19847 50.3%
24.35 123 19970 50.7%
24.3 106 20076 50.9%
24.25 117 20193 51.2%
24.2 118 20311 51.5%
24.15 98 20409 51.8%
24.1 124 20533 52.1%
24.05 121 20654 52.4%
24 110 20764 52.7%
23.95 99 20863 52.9%
23.9 136 20999 53.3%
23.85 128 21127 53.6%
23.8 106 21233 53.9%
23.75 124 21357 54.2%
23.7 100 21457 54.4%
23.65 131 21588 54.8%
23.6 106 21694 55.0%
23.55 125 21819 55.3%
23.5 88 21907 55.6%
23.45 114 22021 55.9%
23.4 113 22134 56.1%
23.35 106 22240 56.4%
23.3 117 22357 56.7%
23.25 121 22478 57.0%
23.2 141 22619 57.4%
23.15 127 22746 57.7%
23.1 113 22859 58.0%
23.05 87 22946 58.2%
23 118 23064 58.5%
22.95 139 23203 58.9%
22.9 129 23332 59.2%
22.85 104 23436 59.4%
22.8 116 23552 59.7%
22.75 123 23675 60.0%
22.7 109 23784 60.3%
22.65 152 23936 60.7%
22.6 124 24060 61.0%
22.55 117 24177 61.3%
22.5 133 24310 61.7%
22.45 107 24417 61.9%
22.4 117 24534 62.2%
22.35 134 24668 62.6%
22.3 131 24799 62.9%
22.25 104 24903 63.2%
22.2 117 25020 63.5%
22.15 139 25159 63.8%
22.1 119 25278 64.1%
22.05 126 25404 64.4%
22 139 25543 64.8%
21.95 116 25659 65.1%
21.9 127 25786 65.4%
21.85 136 25922 65.7%
21.8 136 26058 66.1%
21.75 131 26189 66.4%
21.7 121 26310 66.7%
21.65 131 26441 67.1%
21.6 125 26566 67.4%
21.55 113 26679 67.7%
21.5 134 26813 68.0%
21.45 128 26941 68.3%
21.4 132 27073 68.7%
21.35 129 27202 69.0%
21.3 137 27339 69.3%
21.25 120 27459 69.6%
21.2 121 27580 70.0%
21.15 131 27711 70.3%
21.1 115 27826 70.6%
21.05 122 27948 70.9%
21 126 28074 71.2%
20.95 135 28209 71.5%
20.9 102 28311 71.8%
20.85 119 28430 72.1%
20.8 120 28550 72.4%
20.75 113 28663 72.7%
20.7 118 28781 73.0%
20.65 111 28892 73.3%
20.6 106 28998 73.5%
20.55 112 29110 73.8%
20.5 123 29233 74.1%
20.45 137 29370 74.5%
20.4 124 29494 74.8%
20.35 121 29615 75.1%
20.3 127 29742 75.4%
20.25 108 29850 75.7%
20.2 108 29958 76.0%
20.15 100 30058 76.2%
20.1 114 30172 76.5%
20.05 123 30295 76.8%
20 119 30414 77.1%
19.95 133 30547 77.5%
19.9 101 30648 77.7%
19.85 111 30759 78.0%
19.8 111 30870 78.3%
19.75 105 30975 78.6%
19.7 125 31100 78.9%
19.65 118 31218 79.2%
19.6 123 31341 79.5%
19.55 121 31462 79.8%
19.5 126 31588 80.1%
19.45 87 31675 80.3%
19.4 124 31799 80.7%
19.35 100 31899 80.9%
19.3 145 32044 81.3%
19.25 114 32158 81.6%
19.2 89 32247 81.8%
19.15 102 32349 82.0%
19.1 111 32460 82.3%
19.05 100 32560 82.6%
19 104 32664 82.8%
18.95 114 32778 83.1%
18.9 105 32883 83.4%
18.85 114 32997 83.7%
18.8 113 33110 84.0%
18.75 125 33235 84.3%
18.7 110 33345 84.6%
18.65 118 33463 84.9%
18.6 85 33548 85.1%
18.55 106 33654 85.4%
18.5 111 33765 85.6%
18.45 108 33873 85.9%
18.4 89 33962 86.1%
18.35 148 34110 86.5%
18.3 104 34214 86.8%
18.25 111 34325 87.1%
18.2 91 34416 87.3%
18.15 97 34513 87.5%
18.1 98 34611 87.8%
18.05 120 34731 88.1%
18 102 34833 88.3%
17.95 100 34933 88.6%
17.9 85 35018 88.8%
17.85 86 35104 89.0%
17.8 112 35216 89.3%
17.75 101 35317 89.6%
17.7 93 35410 89.8%
17.65 104 35514 90.1%
17.6 100 35614 90.3%
17.55 108 35722 90.6%
17.5 102 35824 90.9%
17.45 109 35933 91.1%
17.4 82 36015 91.3%
17.35 86 36101 91.6%
17.3 93 36194 91.8%
17.25 83 36277 92.0%
17.2 91 36368 92.2%
17.15 95 36463 92.5%
17.1 92 36555 92.7%
17.05 95 36650 93.0%
17 84 36734 93.2%
16.95 99 36833 93.4%
16.9 75 36908 93.6%
16.85 79 36987 93.8%
16.8 92 37079 94.0%
16.75 85 37164 94.3%
16.7 74 37238 94.4%
16.65 79 37317 94.6%
16.6 65 37382 94.8%
16.55 65 37447 95.0%
16.5 103 37550 95.2%
16.45 77 37627 95.4%
16.4 79 37706 95.6%
16.35 79 37785 95.8%
16.3 69 37854 96.0%
16.25 71 37925 96.2%
16.2 75 38000 96.4%
16.15 95 38095 96.6%
16.1 66 38161 96.8%
16.05 76 38237 97.0%
16 69 38306 97.2%
15.95 67 38373 97.3%
15.9 64 38437 97.5%
15.85 46 38483 97.6%
15.8 67 38550 97.8%
15.75 70 38620 98.0%
15.7 53 38673 98.1%
15.65 60 38733 98.2%
15.6 46 38779 98.4%
15.55 62 38841 98.5%
15.5 68 38909 98.7%
15.45 54 38963 98.8%
15.4 59 39022 99.0%
15.35 60 39082 99.1%
15.3 48 39130 99.2%
15.25 51 39181 99.4%
15.2 55 39236 99.5%
15.15 50 39286 99.6%
15.1 43 39329 99.8%
15.05 50 39379 99.9%
15 48 39427 100.0%