PrakOffstat_Pert2

# ==== Contoh Soal 1 ==== #
library(ggplot2)

data = read.table(file.choose(), header = TRUE)
data

##   Tahun     JP
## 1  1961  97.02
## 2  1971 119.21
## 3  1980 147.49
## 4  1990 179.38
## 5  2000 206.26
## 6  2010 237.63
## 7  2020 270.20

ggplot(data, aes(x = Tahun, y = JP)) +
  geom_line(color = "red", linewidth = 1) +
  geom_point(color = "red", size = 3) +
  labs(
    title = "Perkembangan Jumlah Penduduk Indonesia",
    x = "Tahun",
    y = "Jumlah Penduduk (juta jiwa)"
  ) +
  theme_minimal()

# ==== Contoh Soal 2 ==== #
library(ggplot2)

data = read.table(file.choose(), header = TRUE)
data

##    Kelompok.Umur Laki.laki Perempuan
## 1            0-4  11544034  11086837
## 2            5-9  11315802  10824232
## 3          10-14  11230984  10768809
## 4          15-19  11360036  10710253
## 5          20-24  11375210  10723556
## 6          25-29  11510225  10946835
## 7          30-34  11367516  10891960
## 8          35-39  11079680  10744739
## 9          40-44  10530808  10320815
## 10         45-49   9952692   9892636
## 11         50-54   8955061   9009548
## 12         55-59   7703964   7854501
## 13         60-64   6267477   6512781
## 14         65-69   4696126   4968122
## 15         70-74   3188311   3490743
## 16           75+   2786114   3587976

data$Laki.laki = -data$Laki.laki

data$Kelompok.Umur = factor(
  data$Kelompok.Umur,
  levels = data$Kelompok.Umur
)

ggplot(data, aes(x = Kelompok.Umur)) +
  geom_col(aes(y = Laki.laki), fill = "skyblue") +
  geom_col(aes(y = Perempuan), fill = "pink") +
  coord_flip() +
  scale_y_continuous(labels = abs) +
  labs(
    title = "Piramida Penduduk Indonesia Tahun 2026",
    x = "Kelompok Umur",
    y = "Jumlah Penduduk (jiwa)"
  ) +
  theme_minimal()

# ==== Contoh Soal 3 ==== #
data=read.table(file.choose(),header=T)  
data 

##         Kabupaten.Kota JP2025 JP2026
## 1                Paser  289.8  292.4
## 2          Kutai_Barat  180.3  181.8
## 3    Kutai_Kartanegara  845.6  897.9
## 4          Kutai_Timur  470.4  477.7
## 5                Berau  265.3  268.7
## 6  Penajam_Paser_Utara  400.0  523.3
## 7          Mahakam_Ulu   34.7   35.3
## 8      Kota_Balikpapan  725.4  735.9
## 9       Kota_Samarinda  865.3  872.3
## 10        Kota_Bontang  190.7  193.1

shapiro.test(data$JP2025)  

## 
##  Shapiro-Wilk normality test
## 
## data:  data$JP2025
## W = 0.91012, p-value = 0.2818

shapiro.test(data$JP2026) 

## 
##  Shapiro-Wilk normality test
## 
## data:  data$JP2026
## W = 0.92195, p-value = 0.3735

t.test(data$JP2025,data$JP2026,alternative="two.sided", conf.level=0.95, paired=T)

## 
##  Paired t-test
## 
## data:  data$JP2025 and data$JP2026
## t = -1.7075, df = 9, p-value = 0.1219
## alternative hypothesis: true mean difference is not equal to 0
## 95 percent confidence interval:
##  -49.030189   6.850189
## sample estimates:
## mean difference 
##          -21.09