Lembaga : Universitas Islam Negeri Maulana Malik Ibrahim Malang
Jurusan : Teknik Informatika
library(readxl)
## Warning: package 'readxl' was built under R version 4.1.2
datainflowriau <- read_excel(path = "Riau.xlsx")
datainflowriau
## # A tibble: 11 x 12
## Provinsi `2011` `2012` `2013` `2014` `2015` `2016` `2017` `2018` `2019`
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Sumatera 57900. 65911. 98369. 8.60e4 86549. 97764. 1.04e5 1.17e5 1.34e5
## 2 Aceh 2308. 2620. 36337. 4.57e3 4710. 5775. 5.51e3 5.80e3 7.51e3
## 3 Sumatera Utara 23238. 25981. 18120. 3.05e4 30254. 34427. 3.56e4 4.18e4 4.71e4
## 4 Sumatera Barat 9385. 11192. 14056. 1.41e4 13309. 14078. 1.53e4 1.51e4 1.47e4
## 5 Riau 3012. 4447. 8933. 6.36e3 7156. 8211. 8.55e3 1.07e4 1.09e4
## 6 Kep. Riau 1426. 2236. 3378. 2.56e3 3218. 4317. 4.41e3 5.13e3 6.08e3
## 7 Jambi 1868. 2138. 3047. 5.17e3 4978. 4398. 4.40e3 5.66e3 6.49e3
## 8 Sumatera Sela~ 7820. 9126. 8647. 1.00e4 10797. 12752. 1.31e4 1.43e4 1.48e4
## 9 Bengkulu 1153. 1201. 2378. 3.26e3 2791. 2889. 3.62e3 4.15e3 5.79e3
## 10 Lampung 7690. 6969. 3474. 9.45e3 8160. 9373. 1.21e4 1.34e4 1.70e4
## 11 Kep. Bangka B~ 0 0 0 1.37e1 1177. 1544. 1.16e3 1.52e3 3.27e3
## # ... with 2 more variables: `2020` <dbl>, `2021` <dbl>
library(tidyverse)
## Warning: package 'tidyverse' was built under R version 4.1.2
## -- Attaching packages --------------------------------------- tidyverse 1.3.1 --
## v ggplot2 3.3.5 v purrr 0.3.4
## v tibble 3.1.6 v dplyr 1.0.8
## v tidyr 1.2.0 v stringr 1.4.0
## v readr 2.1.2 v forcats 0.5.1
## Warning: package 'ggplot2' was built under R version 4.1.2
## Warning: package 'tibble' was built under R version 4.1.2
## Warning: package 'tidyr' was built under R version 4.1.2
## Warning: package 'readr' was built under R version 4.1.2
## Warning: package 'purrr' was built under R version 4.1.2
## Warning: package 'dplyr' was built under R version 4.1.2
## Warning: package 'forcats' was built under R version 4.1.2
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
datalongerriau <- datainflowriau %>%
pivot_longer(!Provinsi, names_to = "Tahun", values_to = "Kasus")
datalongerriau
## # A tibble: 121 x 3
## Provinsi Tahun Kasus
## <chr> <chr> <dbl>
## 1 Sumatera 2011 57900.
## 2 Sumatera 2012 65911.
## 3 Sumatera 2013 98369.
## 4 Sumatera 2014 86024.
## 5 Sumatera 2015 86549.
## 6 Sumatera 2016 97764.
## 7 Sumatera 2017 103748.
## 8 Sumatera 2018 117495.
## 9 Sumatera 2019 133762.
## 10 Sumatera 2020 109345.
## # ... with 111 more rows
library(dplyr)
riauup2 <- select(datalongerriau, Provinsi, Kasus)
riauup2
## # A tibble: 121 x 2
## Provinsi Kasus
## <chr> <dbl>
## 1 Sumatera 57900.
## 2 Sumatera 65911.
## 3 Sumatera 98369.
## 4 Sumatera 86024.
## 5 Sumatera 86549.
## 6 Sumatera 97764.
## 7 Sumatera 103748.
## 8 Sumatera 117495.
## 9 Sumatera 133762.
## 10 Sumatera 109345.
## # ... with 111 more rows
library(dplyr)
riauup4 <- datalongerriau %>%
filter(Provinsi == 'Riau') %>%
select('Provinsi', 'Tahun', 'Kasus')
riauup4
## # A tibble: 11 x 3
## Provinsi Tahun Kasus
## <chr> <chr> <dbl>
## 1 Riau 2011 3012.
## 2 Riau 2012 4447.
## 3 Riau 2013 8933.
## 4 Riau 2014 6358.
## 5 Riau 2015 7156.
## 6 Riau 2016 8211.
## 7 Riau 2017 8553.
## 8 Riau 2018 10730.
## 9 Riau 2019 10915.
## 10 Riau 2020 9148.
## 11 Riau 2021 7769.
riauup5 <- datalongerriau %>%
filter(Provinsi == 'Riau', Tahun == '2011') %>%
select('Provinsi', 'Tahun', 'Kasus')
riauup5
## # A tibble: 1 x 3
## Provinsi Tahun Kasus
## <chr> <chr> <dbl>
## 1 Riau 2011 3012.
ggplot(data = datalongerriau, mapping = aes(x = Tahun, y = Kasus)) +
geom_point() +
facet_wrap( ~ Provinsi) +
theme(axis.text.x = element_text(angle = 90))
ggplot(data = datalongerriau, mapping = aes(x = Provinsi, y = Kasus)) +
geom_point() +
facet_wrap( ~ Tahun) +
theme(axis.text.x = element_text(angle = 90))
