Tugas ini dibuat berdasarkan tugas visualisasi time series. Untuk package yang digunakan sebagai berikut :

DATA

Berikut merupakan cuplikan sedikit dari data - data yang dignuakan dalam tugas ini.

BBCA
Tanggal Terakhir Pembukaan Tertinggi Terendah Vol. Perubahan%
16/03/2026 6800 6875 6875 6700 82,14M -1,09%
13/03/2026 6875 6850 7025 6850 107,94M -0,36%
12/03/2026 6900 6825 7025 6825 98,79M 1,10%
11/03/2026 6825 6975 7000 6825 91,92M -2,15%
10/03/2026 6975 6950 7050 6925 129,98M 1,45%
09/03/2026 6875 6900 6950 6825 150,43M -1,79%
06/03/2026 7000 7075 7100 7000 102,73M -1,41%
BBNI
Tanggal Terakhir Pembukaan Tertinggi Terendah Vol. Perubahan%
16/03/2026 4330 4260 4340 4230 75,71M 2,12%
13/03/2026 4240 4290 4310 4220 99,44M -0,93%
12/03/2026 4280 4300 4350 4270 87,01M -0,23%
11/03/2026 4290 4300 4330 4280 54,80M 0,70%
10/03/2026 4260 4350 4370 4250 66,62M -0,70%
09/03/2026 4290 4150 4330 4130 102,38M 0,47%
06/03/2026 4270 4270 4300 4210 47,79M -0,23%
BMRI
Tanggal Terakhir Pembukaan Tertinggi Terendah Vol. Perubahan%
16/03/2026 4720 4730 4740 4640 87,92M -0,63%
13/03/2026 4750 4900 4920 4750 187,46M -4,23%
12/03/2026 4960 4870 4980 4870 85,99M 1,64%
11/03/2026 4880 4930 4970 4880 86,76M -0,61%
10/03/2026 4910 4920 4990 4860 124,58M 1,87%
09/03/2026 4820 4800 4870 4780 217,67M -3,21%
06/03/2026 4980 5075 5100 4950 127,63M -2,83%

TIMES SERIES

Untuk mendapatkan grafik time series, berikut merupakan syntax yang digunakan.

BBCA

#bbca
a <- ggplot(databca, aes(x=Time, y=Price)) +
  geom_line(color = "orange") +
  xlab("Date")
a + scale_x_date(date_labels = "%B %Y", date_breaks = "2 months" )+
  theme_minimal()+
  theme(axis.text.x=element_text(angle=50, hjust=1))+
  geom_vline(xintercept = as.Date(c("2024-01-01", "2025-01-01", "2026-01-01")), 
             linetype = "dashed", color = "black", alpha = 0.6)+
  stat_peaks(geom = "point", span = 15, color = "grey", size = 2) +
  stat_peaks(geom = "label", span = 15, color = "grey", angle = 0,
             hjust = -0.1, x.label.fmt = "%d/%m/%y") +
  stat_peaks(geom = "rug", span = 15, color = "purple", sides = "b")

BBNI

b <- ggplot(databni, aes(x=Time, y=Price)) +
  geom_line(color = "blue") +
  xlab("Date")
b + scale_x_date(date_labels = "%B %Y", date_breaks = "2 months" )+
  theme_minimal()+
  theme(axis.text.x=element_text(angle=50, hjust=1))+
  geom_vline(xintercept = as.Date(c("2024-01-01", "2025-01-01", "2026-01-01")), 
             linetype = "dashed", color = "black", alpha = 0.6)+
  stat_peaks(geom = "point", span = 15, color = "steelblue3", size = 2) +
  stat_peaks(geom = "label", span = 15, color = "steelblue3", angle = 0,
             hjust = -0.1, x.label.fmt = "%d/%m/%y") +
  stat_peaks(geom = "rug", span = 15, color = "blue", sides = "b")

BMRI

#bmri
c <- ggplot(datamri, aes(x=Time, y=Price)) +
  geom_line(color = "red") +
  xlab("Date")
c + scale_x_date(date_labels = "%B %Y", date_breaks = "2 months" )+
  theme_minimal()+
  theme(axis.text.x=element_text(angle=50, hjust=1))+
  geom_vline(xintercept = as.Date(c("2024-01-01", "2025-01-01", "2026-01-01")), 
             linetype = "dashed", color = "black", alpha = 0.6)+
  stat_peaks(geom = "point", span = 15, color = "magenta", size = 2) +
  stat_peaks(geom = "label", span = 15, color = "magenta", angle = 0,
             hjust = -0.1, x.label.fmt = "%d/%m/%y") +
  stat_peaks(geom = "rug", span = 15, color = "black", sides = "b")

Grafik time series diatas memperlihatkan bagaimana perubahan harga tiap saham tiap bulannya.

MULTIPLE GRAHP

Ini merupakan grafik yang mebandingkan pergerakan antara ke-3 saham yang digunakna

BOXPLOT KESELURUHAN

BOXPLOT BERDASARKAN TAHUN

BOXPLOT PER SAHAM