visualisasi dan prediksi data inflow-outflow uang kartal di sumatera utara

library(readxl)
datainflow <- read_excel(path = "Inflowedit.xlsx")
datainflow

## # A tibble: 11 x 12
##    Tahun Sumatera   Aceh `Sumatera Utara` `Sumatera Barat`   Riau `Kep. Riau`
##    <dbl>    <dbl>  <dbl>            <dbl>            <dbl>  <dbl>       <dbl>
##  1  2011   57900.  2308.           23238.            9385.  3012.       1426.
##  2  2012   65911.  2620.           25981.           11192.  4447.       2236.
##  3  2013   98369. 36337.           18120.           14056.  8933.       3378.
##  4  2014   86024.  4567.           30503.           14103.  6358.       2563.
##  5  2015   86549.  4710.           30254.           13309.  7156.       3218.
##  6  2016   97764.  5775.           34427.           14078.  8211.       4317.
##  7  2017  103748.  5514.           35617.           15312.  8553.       4412.
##  8  2018  117495.  5799.           41769.           15058. 10730.       5134.
##  9  2019  133762.  7509.           47112.           14750. 10915.       6077.
## 10  2020  109345.  6641.           36609.           10696.  9148.       6175.
## 11  2021   89270.  3702.           31840.           10748.  7769.       5009.
## # ... with 5 more variables: Jambi <dbl>, `Sumatera Selatan` <dbl>,
## #   Bengkulu <dbl>, Lampung <dbl>, `Kep. Bangka Belitung` <dbl>

datainflow$`Sumatera Utara`

##  [1] 23237.76 25980.64 18120.07 30502.75 30253.58 34426.87 35616.72 41768.66
##  [9] 47112.32 36609.31 31840.25

plot(datainflow$`Sumatera Utara`, type = "l", col = "magenta")

library(readxl)
dataoutflow <- read_excel(path = "outflowedit.xlsx")
dataoutflow

## # A tibble: 11 x 12
##    Tahun Sumatera   Aceh `Sumatera Utara` `Sumatera Barat`   Riau `Kep. Riau`
##    <dbl>    <dbl>  <dbl>            <dbl>            <dbl>  <dbl>       <dbl>
##  1  2011   80092.  6338.           22176.            5300. 12434.       5819.
##  2  2012   85235.  6378.           22495.            6434. 13014.       6966.
##  3  2013  103288. 23278.           19235.            6511. 15460.       8747.
##  4  2014  102338.  8630.           26391.            7060. 15158.      10122.
##  5  2015  109186.  9637.           27877.            7471. 15789.       9803.
##  6  2016  121992. 11311.           31959.            9198. 17645.      10068.
##  7  2017  133606. 11760.           35243.           10754. 18128.      10749.
##  8  2018  135676. 11450.           36908.            8447. 17926.      12597.
##  9  2019  153484. 13087.           44051.            9465. 19277.      12644.
## 10  2020  140589. 12874.           39758.            8763. 19139.       8461.
## 11  2021   86627.  5770.           23453.            5941. 12631.       5128.
## # ... with 5 more variables: Jambi <dbl>, `Sumatera Selatan` <dbl>,
## #   Bengkulu <dbl>, Lampung <dbl>, `Kep. Bangka Belitung` <dbl>

plot(dataoutflow$`Sumatera Utara`, type = "l", col = "magenta")

dataoutflow

## # A tibble: 11 x 12
##    Tahun Sumatera   Aceh `Sumatera Utara` `Sumatera Barat`   Riau `Kep. Riau`
##    <dbl>    <dbl>  <dbl>            <dbl>            <dbl>  <dbl>       <dbl>
##  1  2011   80092.  6338.           22176.            5300. 12434.       5819.
##  2  2012   85235.  6378.           22495.            6434. 13014.       6966.
##  3  2013  103288. 23278.           19235.            6511. 15460.       8747.
##  4  2014  102338.  8630.           26391.            7060. 15158.      10122.
##  5  2015  109186.  9637.           27877.            7471. 15789.       9803.
##  6  2016  121992. 11311.           31959.            9198. 17645.      10068.
##  7  2017  133606. 11760.           35243.           10754. 18128.      10749.
##  8  2018  135676. 11450.           36908.            8447. 17926.      12597.
##  9  2019  153484. 13087.           44051.            9465. 19277.      12644.
## 10  2020  140589. 12874.           39758.            8763. 19139.       8461.
## 11  2021   86627.  5770.           23453.            5941. 12631.       5128.
## # ... with 5 more variables: Jambi <dbl>, `Sumatera Selatan` <dbl>,
## #   Bengkulu <dbl>, Lampung <dbl>, `Kep. Bangka Belitung` <dbl>

plot(datainflow$`Sumatera Utara`, type = "l", col = "red")
lines(dataoutflow$`Sumatera Utara`, type = "l", col = "blue")