Visualisasi Data Inflow dan Outflow Di Kalimantan Tengah
Rafi Ronalda Purnama Hakim,Prof.Dr.Suhartono,M.KOM
2/24/2022
Universitas : UIN MAULANA MALIK IBRAHIM MALANG
Jurusan : Teknik Informatika
Pengertian Inflow dan Outflow pada Uang Kartal
Inflow, disebut investasi sebagai langsung dalam ekonomi pelaporan, termasuk semua kewajiban dan aset yang ditransfer antara perusahaan investasi langsung penduduk dan investor langsung mereka. Ini juga mencakup transfer aset dan kewajiban antara perusahaan yang bertempat tinggal dan yang tidak residen, jika orang tua pengendali utama adalah bukan penduduk.
Outflow, disebut sebagai investasi langsung di luar negeri, termasuk aset dan kewajiban yang ditransfer antara investor langsung penduduk dan perusahaan investasi langsung mereka. Ini juga mencakup transfer aset dan kewajiban antara sesama dan non-residen perusahaan, jika orang tua pengendali utama adalah penduduk. Investasi langsung keluar juga disebut investasi langsung di luar negeri.
library(readxl)datainflow <- read_excel(path = "InflowTahun.xlsx")## New names:
## * `` -> ...2datainflow## # A tibble: 12 x 12
## Keterangan ...2 `Bali Nusra` Bali `Nusa Tenggara Barat` `Nusa Tenggara T~`
## <dbl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 NA NA NA NA NA NA
## 2 2011 NA 10322. 6394. 1803. 2125.
## 3 2012 NA 14613. 8202. 3676. 2735.
## 4 2013 NA 17512. 5066. 7024. 5422.
## 5 2014 NA 20807. 11590. 5704. 3512.
## 6 2015 NA 23008. 13072. 6285. 3651.
## 7 2016 NA 30965. 17914. 8842. 4210.
## 8 2017 NA 30797. 16962. 8383. 5452.
## 9 2018 NA 33866. 18610. 9140. 6116.
## 10 2019 NA 38116. 21422. 9614. 7080.
## 11 2020 NA 29400. 14735. 8007. 6657.
## 12 2021 NA 18892. 7505. 5888. 5498.
## # ... with 6 more variables: Kalimantan <dbl>, `Kalimantan Barat` <dbl>,
## # `Kalimantan Tengah` <dbl>, `Kalimantan Selatan` <dbl>,
## # `Kalimantan Timur` <dbl>, `Kalimantan Utara` <dbl>library (readxl)dataoutflow <- read_excel(path = "OutflowTahun.xlsx")
dataoutflow## # A tibble: 11 x 10
## Tahun Bali `Nusa Tenggara Ba~` `Nusa Tenggara~` Kalimantan `Kalimantan Ba~`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2011 8912. 3819. 3693. 29535. 5221.
## 2 2012 10782. 4379. 4260. 33444. 5698.
## 3 2013 7248. 10628. 11524. 44929. 6011.
## 4 2014 13104. 5620. 4668. 38772. 6764.
## 5 2015 14471. 6728. 5530. 41945. 8486.
## 6 2016 18140. 8149. 5652. 42179. 9402.
## 7 2017 17822. 8770. 7569. 50404. 11132.
## 8 2018 20434. 9271. 7555. 53989. 12278.
## 9 2019 20654. 10288. 7738. 57579. 13768.
## 10 2020 14323. 8546. 8356. 52060. 13501.
## 11 2021 6531. 5222. 3472. 30291. 6958.
## # ... with 4 more variables: `Kalimantan Tengah` <dbl>,
## # `Kalimantan Selatan` <dbl>, `Kalimantan Timur` <dbl>,
## # `Kalimantan Utara` <dbl>dataoutflow## # A tibble: 11 x 10
## Tahun Bali `Nusa Tenggara Ba~` `Nusa Tenggara~` Kalimantan `Kalimantan Ba~`
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2011 8912. 3819. 3693. 29535. 5221.
## 2 2012 10782. 4379. 4260. 33444. 5698.
## 3 2013 7248. 10628. 11524. 44929. 6011.
## 4 2014 13104. 5620. 4668. 38772. 6764.
## 5 2015 14471. 6728. 5530. 41945. 8486.
## 6 2016 18140. 8149. 5652. 42179. 9402.
## 7 2017 17822. 8770. 7569. 50404. 11132.
## 8 2018 20434. 9271. 7555. 53989. 12278.
## 9 2019 20654. 10288. 7738. 57579. 13768.
## 10 2020 14323. 8546. 8356. 52060. 13501.
## 11 2021 6531. 5222. 3472. 30291. 6958.
## # ... with 4 more variables: `Kalimantan Tengah` <dbl>,
## # `Kalimantan Selatan` <dbl>, `Kalimantan Timur` <dbl>,
## # `Kalimantan Utara` <dbl>1. Visualisasi Prediksi Data Inflow Uang Kartal Kalimantan Tengah setiap periode
plot(datainflow$Keterangan,datainflow$`Kalimantan Tengah`,type = "l", col= "steelblue")
2. Visualisasi Prediksi Data outflow Uang Kartal Kalimantan Tengah setiap periode
plot(dataoutflow$Tahun,dataoutflow$`Kalimantan Tengah`,type = "l", col= "red")
3. Visualisasi Prediksi Data Inflow-Outflow Uang Kartal di Kalimantan Tengah Setiap Periode
plot(datainflow$Keterangan,datainflow$`Kalimantan Tengah`,type = "l", col= "steelblue")
lines(dataoutflow$Tahun,dataoutflow$`Kalimantan Tengah`,col="red")
legend("top",c("Inflow","Outflow"),fill=c("green","steelblue"))
4. Visualisasi Prediksi Data Inflow-Outflow Uang Kartal di Kalimantan Tengah Setiap Bulan
library(readxl)datainflowperbulan <- read_excel(path = "InflowBulan.xlsx")## New names:
## * `` -> ...2datainflowperbulan## # A tibble: 128 x 12
## Bulan ...2 `Bali Nusra` Bali `Nusa Tenggara Barat`
## <dttm> <lgl> <dbl> <dbl> <dbl>
## 1 2011-01-01 00:00:00 NA 912. 463. 93.8
## 2 2011-02-01 00:00:00 NA 591. 401. 82.1
## 3 2011-03-01 00:00:00 NA 869. 532. 125.
## 4 2011-04-01 00:00:00 NA 709. 431. 124.
## 5 2011-05-01 00:00:00 NA 754. 474. 113.
## 6 2011-06-01 00:00:00 NA 633. 393. 105.
## 7 2011-07-01 00:00:00 NA 856. 585. 137.
## 8 2011-08-01 00:00:00 NA 607. 328. 136.
## 9 2011-09-01 00:00:00 NA 1965. 1434. 292.
## 10 2011-10-01 00:00:00 NA 874. 522. 184.
## # ... with 118 more rows, and 7 more variables: `Nusa Tenggara Timur` <dbl>,
## # Kalimantan <dbl>, `Kalimantan Barat` <dbl>, `Kalimantan Tengah` <dbl>,
## # `Kalimantan Selatan` <dbl>, `Kalimantan Timur` <dbl>,
## # `Kalimantan Utara` <dbl>dataoutflowperbulan <- read_excel(path = "OutflowBulan.xlsx")
datainflowperbulan## # A tibble: 128 x 12
## Bulan ...2 `Bali Nusra` Bali `Nusa Tenggara Barat`
## <dttm> <lgl> <dbl> <dbl> <dbl>
## 1 2011-01-01 00:00:00 NA 912. 463. 93.8
## 2 2011-02-01 00:00:00 NA 591. 401. 82.1
## 3 2011-03-01 00:00:00 NA 869. 532. 125.
## 4 2011-04-01 00:00:00 NA 709. 431. 124.
## 5 2011-05-01 00:00:00 NA 754. 474. 113.
## 6 2011-06-01 00:00:00 NA 633. 393. 105.
## 7 2011-07-01 00:00:00 NA 856. 585. 137.
## 8 2011-08-01 00:00:00 NA 607. 328. 136.
## 9 2011-09-01 00:00:00 NA 1965. 1434. 292.
## 10 2011-10-01 00:00:00 NA 874. 522. 184.
## # ... with 118 more rows, and 7 more variables: `Nusa Tenggara Timur` <dbl>,
## # Kalimantan <dbl>, `Kalimantan Barat` <dbl>, `Kalimantan Tengah` <dbl>,
## # `Kalimantan Selatan` <dbl>, `Kalimantan Timur` <dbl>,
## # `Kalimantan Utara` <dbl>dataoutflowperbulan## # A tibble: 128 x 11
## Bulan `Bali Nusra` Bali `Nusa Tenggara Barat` `Nusa Tenggara~`
## <dttm> <dbl> <dbl> <dbl> <dbl>
## 1 2011-01-01 00:00:00 423. 177. 194. 51.9
## 2 2011-02-01 00:00:00 482. 353. 40.9 87.6
## 3 2011-03-01 00:00:00 989. 581. 273. 136.
## 4 2011-04-01 00:00:00 1207. 662. 343. 202.
## 5 2011-05-01 00:00:00 1168. 652. 279. 237.
## 6 2011-06-01 00:00:00 1476. 852. 351. 273.
## 7 2011-07-01 00:00:00 1536. 746. 319. 471.
## 8 2011-08-01 00:00:00 3084. 1888. 796. 400.
## 9 2011-09-01 00:00:00 926. 458. 293. 175.
## 10 2011-10-01 00:00:00 1321. 609. 399. 313.
## # ... with 118 more rows, and 6 more variables: Kalimantan <dbl>,
## # `Kalimantan Barat` <dbl>, `Kalimantan Tengah` <dbl>,
## # `Kalimantan Selatan` <dbl>, `Kalimantan Timur` <dbl>,
## # `Kalimantan Utara` <dbl>plot(datainflowperbulan$`Kalimantan Tengah`, type = "l", col = "steelblue")
lines(dataoutflowperbulan$`Kalimantan Tengah`,col="red")
legend("top",c("Inflow","Outflow"),fill=c("steelblue","red"))
KalimantanTengahtimeseries <- datainflowperbulan$`Kalimantan Tengah`
plot.ts(KalimantanTengahtimeseries , type = "l", col = "steelblue")
logKalimantanTengah <- log(datainflowperbulan$`Kalimantan Tengah`)
plot.ts(logKalimantanTengah)
5. Visualisasi Prediksi Data Inflow-Outflow Time Series Uang Kartal di Kalimantan Tengah
KalimantanTengahinflowtimeseries <- ts(datainflowperbulan$`Kalimantan Tengah`, frequency=12, start=c(2011,1))
KalimantanTengahinflowtimeseries## Jan Feb Mar Apr May Jun
## 2011 104.71966 55.78300 64.28767 45.19356 45.99100 74.64779
## 2012 200.06448 102.71009 62.69569 85.78396 71.78199 74.40131
## 2013 3260.09114 1844.80157 1692.10915 1863.09219 1682.08817 1470.77087
## 2014 343.58319 113.46686 91.14619 67.97726 101.82439 109.95170
## 2015 505.84765 247.81308 227.75714 166.65411 224.50076 290.86845
## 2016 615.48752 248.94332 301.05825 179.74887 227.53505 163.75339
## 2017 615.64887 290.03319 287.84964 285.12107 269.17047 59.70408
## 2018 614.70999 265.27654 218.92177 218.32437 175.13672 706.46821
## 2019 704.79912 293.79454 334.74767 338.00939 101.96037 694.81639
## 2020 599.16605 334.57580 265.92791 295.41042 242.40389 555.35972
## 2021 897.47547 385.60604 342.62656 195.70149 703.86907 369.18861
## Jul Aug Sep Oct Nov Dec
## 2011 34.20407 24.01165 212.53945 29.67208 73.33386 14.43373
## 2012 89.07459 123.79065 72.76016 120.00007 102.77912 28.99388
## 2013 1516.74876 5562.79685 136.50999 143.26117 103.04464 52.61722
## 2014 43.70730 432.68781 176.28005 178.22549 149.29007 79.26257
## 2015 661.93813 281.15367 324.12220 245.39273 243.58708 127.26031
## 2016 718.34960 256.10090 250.35439 260.45869 239.35862 233.14767
## 2017 559.23596 335.15250 291.21939 318.95467 243.93971 99.16539
## 2018 377.91376 292.09641 408.36407 341.38267 291.04323 173.49785
## 2019 344.57313 343.42400 395.30119 356.28819 298.37122 179.15194
## 2020 380.22179 428.16861 280.71102 308.13016 322.66512 165.52683
## 2021 285.83449 353.90169KalimantanTengahoutflowtimeseries <- ts(dataoutflowperbulan$`Kalimantan Tengah`, frequency=12, start=c(2011,1))
KalimantanTengahoutflowtimeseries## Jan Feb Mar Apr May Jun
## 2011 166.96487 317.69003 374.58505 590.86801 558.62426 656.83822
## 2012 188.36824 521.86580 606.59282 645.35250 621.03955 736.53471
## 2013 334.06309 934.95441 1176.79359 749.13655 1669.93701 1504.56359
## 2014 50.59388 418.40019 509.53716 615.06420 674.04111 716.05013
## 2015 103.78520 457.98418 542.72339 943.54883 863.42877 966.28878
## 2016 248.09937 490.99534 641.79237 825.50731 902.54396 1685.00615
## 2017 279.33173 662.17443 824.17579 761.64649 1062.90541 1953.69290
## 2018 208.48642 694.31397 879.66655 1090.97217 1410.88233 1894.72089
## 2019 179.86746 829.42215 978.14046 1086.41005 2344.68346 267.78383
## 2020 300.85870 802.71495 1056.72309 1245.36253 1475.81216 527.43374
## 2021 171.52657 517.41353 792.10084 1268.27183 1706.75174 830.40995
## Jul Aug Sep Oct Nov Dec
## 2011 680.86214 1030.23400 174.92215 598.40555 609.19326 1090.75135
## 2012 586.90198 888.35905 338.94427 687.60373 729.47190 1189.55864
## 2013 3436.60987 1926.60961 567.89163 685.52417 858.43876 1576.44228
## 2014 1441.03987 222.64601 630.01354 902.81476 643.41887 1522.21460
## 2015 1492.04480 589.26756 857.11664 810.90558 970.77420 1592.32174
## 2016 600.50628 673.40108 734.64722 809.09298 1001.78663 1517.83930
## 2017 410.52740 955.58965 728.82953 972.18298 1183.97556 1900.39704
## 2018 862.30857 966.64112 906.45189 1113.90573 1100.21645 1911.32636
## 2019 1168.81399 970.44119 821.55275 1034.17156 1133.60516 2076.32208
## 2020 947.76957 901.80664 879.88716 1256.29582 969.59546 2154.03518
## 2021 942.66711 841.68594plot.ts(KalimantanTengahinflowtimeseries)
plot.ts(KalimantanTengahoutflowtimeseries)
KalimantanTengahintimeseriescomponents <- decompose(KalimantanTengahinflowtimeseries)
KalimantanTengahintimeseriescomponents$seasonal## Jan Feb Mar Apr May
## 2011 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2012 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2013 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2014 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2015 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2016 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2017 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2018 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2019 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2020 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2021 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## Jun Jul Aug Sep Oct
## 2011 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2012 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2013 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2014 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2015 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2016 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2017 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2018 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2019 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2020 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2021 34.0293887 80.1720969 410.8362816
## Nov Dec
## 2011 -198.0499023 -293.4538435
## 2012 -198.0499023 -293.4538435
## 2013 -198.0499023 -293.4538435
## 2014 -198.0499023 -293.4538435
## 2015 -198.0499023 -293.4538435
## 2016 -198.0499023 -293.4538435
## 2017 -198.0499023 -293.4538435
## 2018 -198.0499023 -293.4538435
## 2019 -198.0499023 -293.4538435
## 2020 -198.0499023 -293.4538435
## 2021KalimantanTengahouttimeseriescomponents <- decompose(KalimantanTengahoutflowtimeseries)
KalimantanTengahouttimeseriescomponents$seasonal## Jan Feb Mar Apr May Jun
## 2011 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2012 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2013 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2014 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2015 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2016 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2017 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2018 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2019 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2020 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## 2021 -724.799230 -298.578641 -121.371284 -44.696866 290.841388 198.339245
## Jul Aug Sep Oct Nov Dec
## 2011 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2012 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2013 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2014 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2015 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2016 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2017 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2018 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2019 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2020 254.353864 3.263818 -247.781924 -29.279481 -3.928521 723.637631
## 2021 254.353864 3.263818plot(KalimantanTengahintimeseriescomponents$seasonal,type = "l", col = "steelblue")
lines(KalimantanTengahouttimeseriescomponents$seasonal,col="red")
legend("top",c("Inflow","Outflow"),fill=c("steelblue","red"))
plot(KalimantanTengahintimeseriescomponents$trend,type = "l", col = "green")
lines(KalimantanTengahouttimeseriescomponents$trend,col="grey")
legend("top",c("Inflow","Outflow"),fill=c("green","grey"))
plot(KalimantanTengahintimeseriescomponents$random ,type = "l", col = "green")
lines(KalimantanTengahouttimeseriescomponents$random,col="grey")
legend("top",c("Inflow","Outflow"),fill=c("green","grey"))
plot(KalimantanTengahintimeseriescomponents$figure ,type = "l", col = "green")
lines(KalimantanTengahouttimeseriescomponents$figure,col="grey")
legend("top",c("Inflow","Outflow"),fill=c("green","grey"))