install.packages(“esquisse”) install.packages(“ggplot2”) library(esquisse)

data_aps <- read.csv("C:/Users/user/Downloads/APS 2019-2024 Penduduk Usia 2019-2024.csv")
head(data_aps)
##   Tahun Angka.Partisipasi.Sekolah..APS.
## 1  2019                           71.92
## 2  2020                           71.44
## 3  2021                           70.74
## 4  2022                           72.88
## 5  2023                           73.07
## 6  2024                           74.35

#esquisser(data_aps)

library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.4.2
ggplot(data_aps) +
  aes(x = Tahun, y = Angka.Partisipasi.Sekolah..APS.) +
  geom_line(linewidth = 2L, colour = "#0C4C8A") +
  theme_minimal()

data_pembeli <- read.csv("C:/Users/user/Downloads/calonpembelimobil (2).csv")

head(data_pembeli)
##   ID Usia Status Kelamin Memiliki_Mobil Penghasilan..Juta.Rupiah.per.Tahun.
## 1  1   32      1       0              0                                 240
## 2  2   49      2       1              1                                 100
## 3  3   52      1       0              2                                 250
## 4  4   26      2       1              1                                 130
## 5  5   45      3       0              2                                 237
## 6  6   39      2       0              1                                 280
##   Beli_Mobil
## 1          1
## 2          0
## 3          1
## 4          0
## 5          1
## 6          1
library(dplyr)
## Warning: package 'dplyr' was built under R version 4.4.2
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(ggplot2)

data_pembeli %>%
 filter(Usia >= 24L & Usia <= 80L) %>%
 ggplot() +
 aes(x = Usia) +
 geom_histogram(bins = 30L, fill = "#112446") +
 labs(x = "Usia", 
 y = "Frekuensi", title = "Frekuensi Usia Calon Pembeli Mobil") +
 theme_minimal()