Dosen Pengampu : Prof. Dr. Suhartono, M.Kom
Lembaga : Universitas Islam Negeri Maulana Malik Ibrahim Malang
Jurusan : Teknik Informatika
Fakultas : Sains dan Teknologi
Data Inflow-OutFlow Pertahun untuk Wilayah Kalimantan dan Sekitarnya
library(readxl)
## Warning: package 'readxl' was built under R version 4.1.2
datainflow <- read_excel(path = "C:/Users/shafira halmahera/Documents/LINEAR ALGEBRA/Data Perbulan Inflow Kalimantan.xlsx")
datainflowtahun <- datainflow[c(1:12),c(1:6)]
datainflowtahun
library(readxl)
dataoutflow <- read_excel(path = "C:/Users/shafira halmahera/Documents/LINEAR ALGEBRA/Data Perbulan Outflow Kalimantan.xlsx")
dataoutflow
1. Komparasi Visualisasi Prediksi Data Inflow Uang Kartal di Wilayah Kalimantan dan Kalimantan Selatan Setiap Periode
plot(datainflow$Tahun,datainflow$`SKalimantan`,type = "l", col= "dodgerblue")
lines(datainflow$Tahun,datainflow$Riau,col="red")
legend("top",c("Inflow Kllimantan","Kalimantan Selatan"),fill=c("dodgerblue","red"))

2. Komparasi Visualisasi Prediksi Data Outflow Uang Kartal di Wilayah Kalimantan dan Kalimantan Timur Setiap Periode
plot(dataoutflow$Tahun,dataoutflow$`Sumatera Selatan`,type = "l", col= "yellow")
lines(dataoutflow$Tahun,dataoutflow$Riau,col="mediumorchid")
legend("top",c("Outflow Kalimantan Selatan","Kalimantan Timur"),fill=c("yellow","mediumorchid"))

3. Komparasi Visualisasi Prediksi Data Inflow-Outflow Uang Kartal di Wilayah Kalimantan dan Kalimantan Utara Setiap Periode
plot(datainflow$Tahun,datainflow$`Sumatera Selatan`,type = "l", col= "dodgerblue")
lines(datainflow$Tahun,datainflow$Riau,col="red")
lines(dataoutflow$Tahun,dataoutflow$`Sumatera Selatan`, col= "green")
lines(dataoutflow$Tahun,dataoutflow$Riau,col="mediumorchid")
legend("top",c("Inflow Kalimantan Selatan","Inflow Kalimantan Tengah","Outflow Kalimantan Utara","Outflow Kalimantan Timur "),fill=c("dodgerblue","red","green","mediumorchid"))

4. Komparasi Visualisasi Prediksi Data Inflow-Outflow Uang Kartal di Wilayah Kalimantan Setiap Bulan
library(readxl)
datainflowperbulan <- read_excel(path = "C:/Users/shafira halmahera/Documents/LINEAR ALGEBRA/Data Perbulan Inflow Kalimantan.xlsx")
dataoutflowperbulan <- read_excel(path = "C:/Users/shafira halmahera/Documents/LINEAR ALGEBRA/Data Perbulan Outflow Kalimantan.xlsx")
datainflowperbulan
dataoutflowperbulan
KalimantanSelatantimeseries <- datainflowperbulan$`Kalimantan Selatan`
Kalimantantimeseries <- datainflowperbulan$Kalimantan
plot.ts(KalimantanSelatantimeseries , type = "l", col = "cyan")
lines(Kalimantantimeseries , type = "l", col = "darkorchid")
legend("top",c("Kalimantan Selatan Timeseries","Kalimantan Timur Timeseries"),fill=c("cyan","darkorchid"))

plot(datainflowperbulan$`Kalimantan Selatan`, type = "l", col = "tomato")
lines(datainflowperbulan$Kalimantan,col="darkorchid")
lines(dataoutflowperbulan$`Kalimantan Selatan`, col = "green")
lines(dataoutflowperbulan$Kalimantan,col="purple")
legend("top",c("Inflow Kalimantan Selatan","Inflow Kalimantan","Outflow Kalimantan Selatan","Outflow Kalimantan"),fill=c("tomato","darkorchid","green","purple"))

KalimantanSelatantimeseries <- datainflowperbulan$`Kalimantan Selatan`
Kalimantantimeseries <- datainflowperbulan$Kalimantan
plot.ts(KalimantanSelatantimeseries , type = "l", col = "cyan")
lines(Kalimantantimeseries , type = "l", col = "darkorchid")
legend("top",c("Kalimantan Selatan Timeseries","Kalimantan Timeseries"),fill=c("cyan","darkorchid"))

library(TTR)
## Warning: package 'TTR' was built under R version 4.1.2
5. Komparasi Visualisasi Prediksi Data Inflow-Outflow Time Series Uang Kartal di Wilayah Kalimantan
KalimantanSelataninflowtimeseries <- ts(datainflowperbulan$`Kalimantan Selatan`, frequency=12, start=c(2011,1))
Kalimantaninflowtimeseries <- ts(datainflowperbulan$`Kalimantan Selatan`, frequency=12, start=c(2011,1))
KalimantanSelataninflowtimeseries
## 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 353.90169
Kalimantaninflowtimeseries
## 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 353.90169
KalimantanSelatanoutflowtimeseries <- ts(dataoutflowperbulan$`Kalimantan Selatan`, frequency=12, start=c(2011,1))
Kalimantanoutflowtimeseries <- ts(dataoutflowperbulan$Kalimantan, frequency=12, start=c(2011,1))
KalimantanSelatanoutflowtimeseries
## Jan Feb Mar Apr May Jun
## 2011 30.92676 217.58423 331.32386 349.56174 338.01996 442.51594
## 2012 78.01497 251.83107 418.87169 320.11813 425.22442 617.59797
## 2013 53.28767 173.17133 229.16928 159.83154 564.48615 283.19700
## 2014 205.72818 297.56403 516.77520 462.29009 382.51735 459.45448
## 2015 145.86699 280.42443 375.57112 524.22672 390.50958 765.86225
## 2016 119.98024 321.23994 292.72978 483.17704 707.14356 1745.73473
## 2017 220.74825 470.94490 677.64512 803.43306 894.74852 2335.48989
## 2018 119.70985 411.30635 858.73024 569.53375 1311.73154 1745.23677
## 2019 156.83052 402.14036 735.27418 1026.22248 2307.99246 152.81024
## 2020 224.29025 440.09690 646.45724 823.77876 1415.65499 193.26948
## 2021 190.78066 225.12346 535.54389 1199.73199 1406.42748 434.94900
## Jul Aug Sep Oct Nov Dec
## 2011 448.01446 1334.56541 92.18066 396.73570 385.87217 758.37575
## 2012 445.67986 1000.58272 261.36103 475.96294 392.40476 892.19571
## 2013 651.41614 444.49077 318.61750 503.10060 633.13997 1032.20846
## 2014 1415.42457 330.56652 349.73945 507.07185 479.52777 858.19636
## 2015 1404.93564 267.48039 458.42324 540.49000 665.82226 935.00464
## 2016 600.40955 310.76644 397.14109 478.93165 692.11655 1274.95161
## 2017 274.67225 722.23003 431.55757 688.71465 823.43364 1200.64251
## 2018 343.85731 554.01268 415.87756 561.26903 631.11928 953.91478
## 2019 825.93749 641.39639 462.88459 710.51746 804.34719 1001.84450
## 2020 682.30480 352.21086 694.37750 939.31635 760.47623 1049.55259
## 2021 730.85906 468.65727
Kalimantanoutflowtimeseries
## Jan Feb Mar Apr May Jun
## 2011 582.2242 859.0178 1570.2218 2337.0253 2019.1669 2439.1742
## 2012 834.9211 1409.7713 2125.2689 2378.9988 2628.5642 2954.4279
## 2013 1035.3895 1808.5302 2731.7646 2153.8350 3810.3190 3437.1400
## 2014 948.7785 1379.0510 2511.3898 2746.2057 2713.3284 2831.2588
## 2015 686.6159 1783.9609 2295.2388 3361.3209 3013.7731 4325.7830
## 2016 818.7089 1925.1134 2081.6134 3036.3231 3907.9318 8764.1853
## 2017 1552.3718 2485.4757 3262.4454 3459.7874 4157.8382 10832.3521
## 2018 817.5598 2849.7438 3927.9008 3676.1021 7041.7074 9637.7045
## 2019 1235.8249 2929.3173 3734.6734 5220.7579 13438.4430 856.1754
## 2020 1568.3579 2566.7644 3898.8501 5176.8640 7565.9636 1546.9692
## 2021 618.8893 2150.0993 3163.2461 6284.5272 7612.7585 3140.4786
## Jul Aug Sep Oct Nov Dec
## 2011 2543.5871 6258.0677 671.3997 2174.8158 2631.5086 5448.2917
## 2012 2834.8268 5112.4519 1065.1376 3006.8743 2832.1058 6260.9022
## 2013 8871.1225 4572.3990 2069.9639 3150.6647 3557.6844 7730.3153
## 2014 8509.6390 1072.7505 2499.2401 3501.1177 2882.1789 7177.1445
## 2015 7950.5142 1569.0496 2818.2509 3058.4110 3782.5731 7299.3565
## 2016 2815.3950 2328.2286 3181.5704 2887.3519 3873.3004 6559.2052
## 2017 1396.5417 4158.7154 2746.5025 3688.0760 4964.1545 7699.4466
## 2018 2665.5558 4053.4685 3024.6391 3960.9865 4382.4883 7951.2099
## 2019 4475.0908 4230.7453 3322.1716 4185.1525 4989.9148 8960.7725
## 2020 4100.4353 3203.6999 3570.6942 5348.0481 4276.5758 9237.0826
## 2021 4112.9850 3207.9518
plot.ts(KalimantanSelataninflowtimeseries,type = "l", col = "khaki")
lines(Kalimantaninflowtimeseries, type = "l", col = "sienna")
legend("top",c("KalimantanSelataninflowtimeseries","Kalimantannflowtimeseries"),fill=c("khaki","sienna"))

KalimantanSelatanintimeseriescomponents <- decompose(KalimantanSelataninflowtimeseries)
Kalimantanintimeseriescomponents <- decompose(Kalimantaninflowtimeseries)
KalimantanSelatanintimeseriescomponents$seasonal
## Jan Feb Mar Apr May
## 2011 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2012 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2013 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2014 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2015 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2016 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2017 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2018 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2019 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2020 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## 2021 424.6520534 -0.7561956 -31.6108601 -31.2258212 -78.5270515
## Jun Jul Aug Sep Oct
## 2011 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2012 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2013 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2014 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2015 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2016 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2017 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2018 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2019 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2020 34.0293887 80.1720969 410.8362816 -144.8198416 -171.2463046
## 2021 34.0293887 80.1720969 410.8362816
## Nov Dec
## 2011 -198.0499023 -293.4538435
## 2012 -198.0499023 -293.4538435
## 2013 -198.0499023 -293.4538435
## 2014 -198.0499023 -293.4538435
## 2015 -198.0499023 -293.4538435
## 2016 -198.0499023 -293.4538435
## 2017 -198.0499023 -293.4538435
## 2018 -198.0499023 -293.4538435
## 2019 -198.0499023 -293.4538435
## 2020 -198.0499023 -293.4538435
## 2021
Kalimantanintimeseriescomponents$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
## 2021
KalimantanSelatanouttimeseriescomponents <- decompose(KalimantanSelatanoutflowtimeseries)
Kalimantanouttimeseriescomponents <- decompose(Kalimantanoutflowtimeseries)
KalimantanSelatanouttimeseriescomponents$seasonal
## Jan Feb Mar Apr May Jun
## 2011 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2012 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2013 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2014 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2015 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2016 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2017 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2018 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2019 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2020 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## 2021 -468.949094 -290.659144 -77.279644 -35.758681 318.594760 304.250690
## Jul Aug Sep Oct Nov Dec
## 2011 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2012 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2013 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2014 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2015 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2016 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2017 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2018 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2019 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2020 108.326682 -5.805776 -214.302308 -26.700598 11.920287 376.362827
## 2021 108.326682 -5.805776
Kalimantanouttimeseriescomponents$seasonal
## Jan Feb Mar Apr May Jun
## 2011 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2012 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2013 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2014 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2015 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2016 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2017 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2018 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2019 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2020 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## 2021 -2825.07684 -1701.86621 -813.75865 -326.19998 1547.90126 1179.20313
## Jul Aug Sep Oct Nov Dec
## 2011 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2012 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2013 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2014 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2015 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2016 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2017 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2018 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2019 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2020 895.53166 -70.31379 -1241.33156 -265.22422 16.11986 3605.01535
## 2021 895.53166 -70.31379
plot(KalimantanSelatanintimeseriescomponents$seasonal,type = "l", col = "purple")
lines(Kalimantanintimeseriescomponents$seasonal,col="palegreen")
lines(KalimantanSelatanouttimeseriescomponents$seasonal, type = "l", col = "lightskyblue")
lines(Kalimantanouttimeseriescomponents$seasonal,col="orange")
legend("top",c("Kalimantan Selatan Inflow","Kalimantan Inflow", "Kalimantan Selatan Outflow","Kalimantan Outflow"),fill=c("purple","palegreen","lightskyblue","orange"))

plot(KalimantanSelatanintimeseriescomponents$trend,type = "l", col = "purple")
lines(Kalimantanintimeseriescomponents$trend,col="palegreen")
lines(KalimantanSelatanouttimeseriescomponents$trend, type = "l", col = "lightskyblue")
lines(Kalimantanouttimeseriescomponents$trend,col="orange")
legend("top",c("Kalimantan Selatan Inflow","Kalimantan Inflow", "Kalimantan Selatan Outflow","Kalimantan Outflow"),fill=c("purple","palegreen","lightskyblue","red"))

plot(KalimantanSelatanintimeseriescomponents$random,type = "l", col = "purple")
lines(Kalimantanintimeseriescomponents$random,col="palegreen")
lines(KalimantanSelatanouttimeseriescomponents$random, type = "l", col = "lightskyblue")
lines(Kalimantanouttimeseriescomponents$random,col="orange")
legend("top",c("Kalimantan Selatan Inflow","Kalimantan Inflow", "Kalimatan Selatan Outflow","Kalimantan Outflow"),fill=c("purple","palegreen","lightskyblue","orange"))

plot(KalimantanSelatanintimeseriescomponents$figure,type = "l", col = "purple")
lines(Kalimantanintimeseriescomponents$figure,col="palegreen")
lines(KalimantanSelatanouttimeseriescomponents$figure, type = "l", col = "lightskyblue")
lines(Kalimantanouttimeseriescomponents$figure,col="orange")
legend("top",c("Kalimantan Selatan Inflow","Kalimantan Inflow", "Kalimantan Selatan Outflow","Kalimantan Outflow"),fill=c("purple","palegreen","lightskyblue","blue"))
