Ambil Kelompok Beresiko

library(dplyr)

## 
## 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

# Misal data kamu bernama df
df_sulawesi_perempuan_20_24 <- data_susenas %>%
  filter(
    R405 == 2,                # Jenis kelamin: Perempuan
    R407 >= 20 & R407 <= 24,  # Umur 20–24 tahun
    R101 %in% c(71, 72, 73, 74, 75, 76)  # Provinsi di Pulau Sulawesi
  )

library(dplyr)
library(stringr)

df_sulawesi_perempuan_20_24 <- df_sulawesi_perempuan_20_24 %>%
  mutate(
    kode_kab = str_c(
      str_pad(R101, width = 2, side = "left", pad = "0"),
      str_pad(R102, width = 2, side = "left", pad = "0")
    )
  )

Hasil Per Kabupaten/Kota

library(dplyr)

hasil_proporsi <- df_sulawesi_perempuan_20_24 %>%
  group_by(kode_kab) %>%
  summarise(
    total_perempuan = n(),
    kawin_dini = sum(R409 < 18, na.rm = TRUE),
    proporsi_kawin_dini = kawin_dini / total_perempuan ## Direct Estimate ???
  ) %>%
  ungroup()
hasil_proporsi

## # A tibble: 81 × 4
##    kode_kab total_perempuan kawin_dini proporsi_kawin_dini
##    <chr>              <int>      <int>               <dbl>
##  1 7101                  51          3              0.0588
##  2 7102                  61          4              0.0656
##  3 7103                  47          8              0.170 
##  4 7104                  41          3              0.0732
##  5 7105                  34          7              0.206 
##  6 7106                  66          5              0.0758
##  7 7107                  45          5              0.111 
##  8 7108                  52          7              0.135 
##  9 7109                  47         14              0.298 
## 10 7110                  61         10              0.164 
## # ℹ 71 more rows

Peta Choropleth Proporsi Kawin Dini di Pulau Sulawesi

# --- 1. Library yang diperlukan
library(sf)

## Linking to GEOS 3.13.1, GDAL 3.11.0, PROJ 9.6.0; sf_use_s2() is TRUE

library(dplyr)
library(leaflet)

# --- 2. Baca shapefile kabupaten/kota seluruh Indonesia
shp_path <- "C:/Users/User/Documents/AKA/LIVING YOUNG AND F'CK SKRIPSI/Pengolahan/R Studio/GeoData/Kab/kab_20201_byindo.shp"
kab_sf <- st_read(shp_path)

## Reading layer `kab_20201_byindo' from data source 
##   `C:\Users\User\Documents\AKA\LIVING YOUNG AND F'CK SKRIPSI\Pengolahan\R Studio\GeoData\Kab\kab_20201_byindo.shp' 
##   using driver `ESRI Shapefile'
## Simple feature collection with 517 features and 8 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: 95.01112 ymin: -11.00731 xmax: 141.02 ymax: 6.076809
## Geodetic CRS:  WGS 84

# --- 3. Filter hanya provinsi di Pulau Sulawesi
prov_sulawesi <- c(
  "SULAWESI UTARA", "SULAWESI TENGAH", "SULAWESI SELATAN",
  "SULAWESI TENGGARA", "GORONTALO", "SULAWESI BARAT"
)

kab_sf_sulawesi <- kab_sf %>%
  filter(nmprov %in% prov_sulawesi)

# --- 4. Pastikan tipe kode sama dan gabungkan dengan hasil_proporsi
kab_sf_sulawesi <- kab_sf_sulawesi %>%
  mutate(idkab = as.numeric(idkab))

hasil_proporsi <- hasil_proporsi %>%
  mutate(kode_kab = as.numeric(kode_kab))

sulawesi_join <- kab_sf_sulawesi %>%
  left_join(hasil_proporsi, by = c("idkab" = "kode_kab"))

# --- 5. Buat palet warna dan popup info
pal <- colorNumeric(palette = "YlOrRd", domain = sulawesi_join$proporsi_kawin_dini)

sulawesi_join$popup_info <- paste0(
  "<b>", sulawesi_join$nmkab, "</b><br>",
  "Provinsi: ", sulawesi_join$nmprov, "<br>",
  "Total perempuan: ", formatC(sulawesi_join$total_perempuan, big.mark = ","), "<br>",
  "Kawin dini: ", formatC(sulawesi_join$kawin_dini, big.mark = ","), "<br>",
  "Proporsi kawin dini: ", round(sulawesi_join$proporsi_kawin_dini * 100, 2), "%"
)

# --- 6. Buat peta interaktif
leaflet(sulawesi_join) %>%
  addProviderTiles(providers$CartoDB.Positron) %>%
  addPolygons(
    fillColor = ~pal(proporsi_kawin_dini),
    weight = 1,
    color = "white",
    fillOpacity = 0.8,
    highlight = highlightOptions(weight = 2, color = "black", bringToFront = TRUE),
    label = ~nmkab,
    popup = ~popup_info
  ) %>%
  addLegend(
    position = "bottomright",
    pal = pal,
    values = ~proporsi_kawin_dini,
    title = "Proporsi Kawin Dini",
    opacity = 1
  )

Visualisasi Sebaran Normalisasi (0-1)

hasil_proporsi <- hasil_proporsi %>%
  mutate(proporsi_norm = (proporsi_kawin_dini - min(proporsi_kawin_dini, na.rm = TRUE)) /
                           (max(proporsi_kawin_dini, na.rm = TRUE) - min(proporsi_kawin_dini, na.rm = TRUE)))


library(ggplot2)

ggplot(hasil_proporsi, aes(x = proporsi_norm)) +
  geom_density(fill = "#2E86AB", alpha = 0.5, color = "#1B4F72", linewidth = 1.2) +
  labs(
    title = "Distribusi Proporsi Normalisasi Perempuan 20–24 Tahun yang Menikah Sebelum 18 Tahun",
    subtitle = "Per Kabupaten/Kota di Pulau Sulawesi",
    x = "Proporsi Kawin Dini (Ternormalisasi)",
    y = "Kepadatan (Density)"
  ) +
  theme_minimal(base_size = 13)

Visualisasi Sebaran Normalisasi Z-Score

hasil_proporsi <- hasil_proporsi %>%
  mutate(proporsi_z = (proporsi_kawin_dini - mean(proporsi_kawin_dini, na.rm = TRUE)) /
                        sd(proporsi_kawin_dini, na.rm = TRUE))
library(ggplot2)

ggplot(hasil_proporsi, aes(x = proporsi_z)) +
  geom_density(fill = "#3498DB", alpha = 0.5, color = "#1F618D", linewidth = 1.2) +
  geom_vline(aes(xintercept = 0), color = "red", linetype = "dashed", linewidth = 1) +
  labs(
    title = "Distribusi Z-Score Proporsi Kawin Dini (Usia <18 Tahun)",
    subtitle = "Perempuan 20–24 Tahun per Kabupaten/Kota di Pulau Sulawesi",
    x = "Z-Score Proporsi Kawin Dini",
    y = "Kepadatan (Density)"
  ) +
  theme_minimal(base_size = 13)

Persiapan Data

# --- Library yang diperlukan ---
library(haven)
library(dplyr)
library(purrr)  
# --- Baca data ---
Podes21_1 <- read_sav("C:/Users/User/Documents/AKA/LIVING YOUNG AND F'CK SKRIPSI/Referensi/SAE Project Based/Data/3. Auxiliary Variable/PODES21_auxvar_1.sav")
Podes21_2 <- read_sav("C:/Users/User/Documents/AKA/LIVING YOUNG AND F'CK SKRIPSI/Referensi/SAE Project Based/Data/3. Auxiliary Variable/PODES21_auxvar_2.sav")
Podes21_3 <- read_sav("C:/Users/User/Documents/AKA/LIVING YOUNG AND F'CK SKRIPSI/Referensi/SAE Project Based/Data/3. Auxiliary Variable/PODES21_auxvar_3.sav")
Podes21_4 <- read_sav("C:/Users/User/Documents/AKA/LIVING YOUNG AND F'CK SKRIPSI/Referensi/SAE Project Based/Data/3. Auxiliary Variable/PODES21_auxvar_4.sav")

# --- Fungsi untuk menambahkan kode_desa ---
add_kode_desa <- function(df) {
  df %>%
    mutate(
      kode_desa = paste0(r101, r102, r103, r104)
    )
}

# --- Tambahkan kode_desa ke tiap dataset ---
Podes21_1 <- add_kode_desa(Podes21_1)
Podes21_2 <- add_kode_desa(Podes21_2)
Podes21_3 <- add_kode_desa(Podes21_3)
Podes21_4 <- add_kode_desa(Podes21_4)

# --- Gabungkan semua data ---
# Gunakan full_join bertahap untuk mempertahankan semua kolom dan semua baris unik
Podes21_all <- list(Podes21_1, Podes21_2, Podes21_3, Podes21_4) %>%
  reduce(function(x, y) full_join(x, y, by = "kode_desa"))

# --- Hilangkan kolom duplikat (misalnya karena suffix .x / .y) ---
# Prioritaskan kolom pertama yang muncul
Podes21_all <- Podes21_all %>%
  select(!matches("\\.y$")) %>%
  rename_with(~ gsub("\\.x$", "", .x))

# --- Hasil akhir ---
glimpse(Podes21_all)

## Rows: 84,096
## Columns: 502
## $ D_R        <chr> "", "", "", "", "", "", "", "", "", "", "", "", "", "", "",…
## $ r101       <chr> "11", "11", "11", "11", "11", "11", "11", "11", "34", "34",…
## $ r101n      <chr> "Aceh", "Aceh", "Aceh", "Aceh", "Aceh", "Aceh", "Aceh", "Ac…
## $ r102       <chr> "01", "01", "01", "01", "01", "01", "01", "01", "01", "01",…
## $ r102n      <chr> "Simeulue", "Simeulue", "Simeulue", "Simeulue", "Simeulue",…
## $ r103       <chr> "010", "010", "010", "010", "010", "010", "010", "010", "07…
## $ r103n      <chr> "Teupah Selatan", "Teupah Selatan", "Teupah Selatan", "Teup…
## $ r104       <chr> "001", "002", "003", "004", "005", "006", "007", "008", "00…
## $ r104n      <chr> "Latiung", "Labuhan Bajau", "Suak Lamatan", "Ana Ao", "Lata…
## $ r105       <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r106b      <dbl> 1109072008, 1109072011, 1109072002, 1109072013, 1109072014,…
## $ r305a      <dbl> 3, 3, 2, 2, 2, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3,…
## $ r305b      <dbl> NA, NA, 2, 2, 2, NA, NA, NA, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, …
## $ r307b2     <dbl> 39.0, 21.8, 15.0, 14.1, 27.0, 41.0, 20.0, 16.0, 120.0, 39.6…
## $ r309a      <dbl> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3,…
## $ r402a      <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r402b1     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 5, 10, 2, 6, 8, 16, 3, 0, 1…
## $ r402b2     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 2, 25, 11, 14, 7, 17, 10, 2…
## $ r402d      <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2,…
## $ r403a      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r403b      <dbl> 1, 1, 1, 14, 1, 10, 8, 8, 1, 8, 8, 8, 8, 8, 8, 1, 1, 10, 1,…
## $ r403d2k2   <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r501a1     <dbl> 72, 136, 153, 161, 145, 124, 83, 123, 1982, 2769, 3126, 214…
## $ r501a2     <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r501b      <dbl> 0, 0, 0, 6, 0, 7, 0, 2, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,…
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## $ r502c      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1,…
## $ r503a3     <dbl> 6, 6, 6, 6, 6, 6, 6, 6, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,…
## $ r503b      <dbl> 10, 7, 10, 10, 10, 10, 10, 7, 4, 10, 4, 10, 10, 10, 4, 4, 4…
## $ r504d      <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 2, 1, 2, 2, 2, 1,…
## $ r507a      <dbl> 2, 2, 2, 9, 2, 2, 2, 2, 7, 6, 3, 3, 7, 7, 7, 7, 7, 7, 6, 6,…
## $ r507b      <dbl> 3, 4, 4, 4, 4, 4, 7, 7, 5, 4, 1, 1, 5, 5, 5, 5, 5, 5, 4, 4,…
## $ r508c1     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r508c2     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r508c3     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r509b9k2   <dbl> 2, 2, 2, 2, 2, 2, 2, NA, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, N…
## $ r509b9k4   <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, …
## $ r509b9k5   <dbl> NA, NA, NA, NA, 2, NA, NA, NA, 2, NA, NA, NA, 2, NA, NA, 2,…
## $ r510a      <dbl> 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r510b1     <dbl> NA, NA, 2, NA, NA, NA, NA, NA, NA, NA, 5, NA, NA, NA, NA, N…
## $ r510b2     <dbl> NA, NA, 11, NA, NA, NA, NA, NA, NA, NA, 100, NA, NA, NA, NA…
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## $ r510c1     <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r510c2a    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r510c2b    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r510c2c    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r511b      <dbl> 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 3, 0, 0, 1, 0, 0, 0, 0,…
## $ r512a      <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r512b1     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r512b2     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r512b3     <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r513ak2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2,…
## $ r513ak3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, …
## $ r513ak4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, …
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## $ r513bk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r513bk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r513ck2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1,…
## $ r513ck3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r513ck4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r514b      <dbl> 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 1, 3, 3, 1, 3, 3, 3, 3, 3, 3,…
## $ r601ak2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1, 2, 2,…
## $ r601ak3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, 4, 2, NA, 3,…
## $ r601ak4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, NA, 0,…
## $ r601ak5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, 0, 1, NA, 0,…
## $ r601ak6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, 0, 0, NA, 0,…
## $ r601bk2    <dbl> 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r601bk3    <dbl> NA, NA, 4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r601bk4    <dbl> NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r601bk5    <dbl> NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r601bk6    <dbl> NA, NA, 0, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r601ck2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r601ck3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ck4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ck5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ck6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601dk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r601dk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601dk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601dk5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601dk6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ek2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r601ek3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ek4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ek5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ek6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601fk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r601fk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601fk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601fk5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601fk6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601gk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r601gk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, …
## $ r601gk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, …
## $ r601gk5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, …
## $ r601gk6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, NA, NA, …
## $ r601hk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r601hk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601hk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601hk5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601hk6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ik2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r601ik3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ik4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ik5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601ik6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601jk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1,…
## $ r601jk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, …
## $ r601jk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, …
## $ r601jk5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, …
## $ r601jk6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0, NA, NA, NA, NA, …
## $ r601kk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r601kk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601kk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601kk5    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r601kk6    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r602       <dbl> NA, NA, 24, NA, NA, NA, NA, NA, 7, NA, 1000, NA, 40, 22, NA…
## $ kode_desa  <chr> "1101010001", "1101010002", "1101010003", "1101010004", "11…
## $ r701ak2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701ak3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 10, 11, 16, 12, 11, 15, 13, 15, 9, …
## $ r701ak4    <dbl> 7, 50, 28, 30, 26, 20, 39, 37, NA, NA, NA, NA, NA, NA, NA, …
## $ r701ak5    <dbl> 1, 2, 1, 1, 1, 1, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r701ak6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r701ak7    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r701ak8    <dbl> 2, 3, 2, 3, 3, 3, 2, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r701bk2    <dbl> 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 2, 0, 1, 0, 1, 0,…
## $ r701bk3    <dbl> 0, 0, 1, 1, 0, 0, 0, 1, 3, 5, 3, 4, 2, 4, 7, 4, 7, 4, 1, 3,…
## $ r701bk4    <dbl> 1, NA, NA, NA, 4, 7, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ r701bk5    <dbl> 1, NA, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ r701bk6    <dbl> 2, NA, NA, NA, 2, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ r701bk7    <dbl> 1, NA, NA, NA, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ r701bk8    <dbl> 1, NA, NA, NA, 2, 2, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA…
## $ r701ck2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701ck3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1,…
## $ r701ck4    <dbl> 99.8, 50.0, 28.0, 30.0, 26.0, 20.0, 99.8, 99.8, 4.5, 1.1, 4…
## $ r701ck5    <dbl> 2, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, NA, NA, 1, 1, 1, NA, 1,…
## $ r701ck6    <dbl> 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 1, 2, NA, NA, 2, 2, 2, NA, 2,…
## $ r701ck7    <dbl> 2, 2, 2, 2, 2, 2, NA, 2, NA, NA, NA, 2, NA, NA, 1, 1, 1, NA…
## $ r701ck8    <dbl> 3, 3, 2, 3, 3, 3, 3, 3, 2, 2, 2, 2, NA, NA, 2, 2, 2, NA, 2,…
## $ r701dk2    <dbl> 1, 1, 1, 1, 1, 1, 0, 1, 5, 8, 4, 8, 4, 8, 5, 6, 4, 3, 3, 5,…
## $ r701dk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 2, 1, 0, 1, 0, 2, 0, 0,…
## $ r701dk4    <dbl> NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r701dk5    <dbl> NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r701dk6    <dbl> NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r701dk7    <dbl> NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r701dk8    <dbl> NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r701ek2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701ek3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 2, 0, 0, 0, 0, 1, 0, 0,…
## $ r701ek4    <dbl> 8.0, 3.0, 1.0, 7.0, 11.0, 20.0, 3.0, 2.0, 10.0, 5.5, NA, 6.…
## $ r701ek5    <dbl> 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, NA, 1, NA, 1, 1, 1, 1, NA, 1,…
## $ r701ek6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, NA, 1, NA, 2, 2, 2, 2, NA, 2,…
## $ r701ek7    <dbl> 2, 1, 1, 1, 2, 2, 2, 2, NA, NA, NA, NA, NA, 2, 2, 1, 1, NA,…
## $ r701ek8    <dbl> 2, 1, 1, 2, 3, 3, 1, 1, 2, 2, NA, 2, NA, 2, 2, 2, 2, NA, 2,…
## $ r701fk2    <dbl> 0, 0, 0, 1, 1, 0, 1, 0, 2, 0, 1, 0, 1, 1, 2, 1, 1, 0, 0, 0,…
## $ r701fk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0,…
## $ r701fk4    <dbl> 1.0, 2.0, 1.0, NA, NA, 3.0, NA, 1.0, NA, NA, NA, 2.1, NA, N…
## $ r701fk5    <dbl> 1, 1, 1, NA, NA, 1, NA, 1, NA, NA, NA, 1, NA, NA, NA, NA, N…
## $ r701fk6    <dbl> 2, 2, 2, NA, NA, 2, NA, 2, NA, NA, NA, 1, NA, NA, NA, NA, N…
## $ r701fk7    <dbl> 1, 1, 1, NA, NA, 1, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ r701fk8    <dbl> 1, 1, 1, NA, NA, 2, NA, 1, NA, NA, NA, 2, NA, NA, NA, NA, N…
## $ r701gk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1,…
## $ r701gk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701gk4    <dbl> 10.0, 19.0, 1.0, 29.0, 26.0, 20.0, 6.0, 5.0, 6.0, 4.0, 3.5,…
## $ r701gk5    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, 1, N…
## $ r701gk6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, NA, 2, 2, 2, 2, N…
## $ r701gk7    <dbl> 2, 1, 1, 2, 2, 2, 2, 2, NA, NA, NA, NA, 1, NA, NA, 1, 1, 1,…
## $ r701gk8    <dbl> 2, 3, 1, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, NA, 2, 2, 2, 2, N…
## $ r701hk2    <dbl> 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0,…
## $ r701hk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701hk4    <dbl> 2.0, 3.0, NA, 1.0, NA, 4.0, NA, 1.0, 6.5, 7.0, NA, 9.0, 3.0…
## $ r701hk5    <dbl> 1, 1, NA, 1, NA, 1, NA, 1, 1, 1, NA, 1, 1, 1, 1, NA, 1, 1, …
## $ r701hk6    <dbl> 2, 2, NA, 2, NA, 2, NA, 2, 1, 1, NA, 1, 2, 1, 2, NA, 2, 2, …
## $ r701hk7    <dbl> 2, 1, NA, 1, NA, 1, NA, 1, NA, NA, NA, NA, 1, NA, 1, NA, 1,…
## $ r701hk8    <dbl> 1, 1, NA, 1, NA, 2, NA, 1, 2, 2, NA, 2, 2, 2, 2, NA, 2, 2, …
## $ r701ik2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701ik3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701ik4    <dbl> 10.0, 19.0, 1.0, 29.0, 26.0, 20.0, 6.0, 5.0, 6.6, 9.8, 4.9,…
## $ r701ik5    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r701ik6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2,…
## $ r701ik7    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, NA, NA, 1, 1, 1, 1,…
## $ r701ik8    <dbl> 2, 3, 1, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r701jk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,…
## $ r701jk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701jk4    <dbl> 10.0, 19.0, 1.0, 29.0, 31.0, 25.0, 6.0, 5.0, 7.3, 6.0, NA, …
## $ r701jk5    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, NA, 1, 1, 1, 1, …
## $ r701jk6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, NA, 1, 2, 1, NA, 2, 2, 2, 2, …
## $ r701jk7    <dbl> 2, 2, 1, 2, 2, 2, 2, 2, NA, NA, NA, NA, 1, NA, NA, 1, 1, 1,…
## $ r701jk8    <dbl> 2, 3, 1, 3, 3, 3, 2, 2, 2, 2, NA, 2, 2, 2, NA, 2, 2, 2, 2, …
## $ r701kk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701kk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701kk4    <dbl> 41.0, 50.0, 28.0, 30.0, 26.0, 20.0, 39.0, 37.0, 7.8, 16.8, …
## $ r701kk5    <dbl> 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r701kk6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2,…
## $ r701kk7    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, 1, NA, 1, 1, 1, 1, …
## $ r701kk8    <dbl> 2, 3, 2, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r701lk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701lk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701mk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701mk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701nk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701nk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701ok2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r701ok3    <dbl> 0, 0, 0, 1, 0, 0, 0, 0, 0, 2, 3, 0, 0, 1, 0, 0, 1, 1, 0, 1,…
## $ r701pk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0,…
## $ r701qk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r702a      <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r702b      <dbl> 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4,…
## $ r703ak2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703ak3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703bk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703bk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703ck2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703ck3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703dk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703dk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703ek2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703ek3    <dbl> 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703fk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703fk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703gk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r703gk3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r704ak2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r704ak3    <dbl> 41.0, 50.0, 28.0, 30.0, 26.0, 20.0, 39.0, 37.0, 9.9, 6.0, 4…
## $ r704ak4    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1,…
## $ r704ak5    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2,…
## $ r704ak6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, 1, NA, 1, 1, 1, 1, …
## $ r704ak7    <dbl> 2, 3, 2, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r704bk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r704bk3    <dbl> 99.8, 99.8, 99.8, 99.8, 99.8, 99.8, 99.8, 99.8, 30.0, 39.0,…
## $ r704bk4    <dbl> 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1,…
## $ r704bk5    <dbl> 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2,…
## $ r704bk6    <dbl> 2, NA, 2, NA, NA, NA, 2, NA, NA, NA, NA, NA, NA, NA, 2, 2, …
## $ r704bk7    <dbl> 3, 4, 3, 4, 4, 4, 3, 3, 2, 2, 2, 2, 2, 2, 2, 4, 2, 2, 2, 2,…
## $ r704ck2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,…
## $ r704ck3    <dbl> 11.0, 3.0, 28.0, 7.0, 11.0, 18.0, 13.0, 15.0, 12.0, 4.0, 6.…
## $ r704ck4    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, NA, 1, 1, 1, 1, 1…
## $ r704ck5    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, NA, 2, 2, 2, 2, 2…
## $ r704ck6    <dbl> 2, 1, 2, 1, 2, 2, 2, 2, NA, NA, NA, NA, 1, NA, NA, 1, 1, 1,…
## $ r704ck7    <dbl> 2, 1, 2, 2, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, NA, 2, 2, 2, 2, 2…
## $ r704dk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0,…
## $ r704dk3    <dbl> 41.0, 50.0, 23.0, 30.0, 26.0, 20.0, 39.0, 37.0, 5.0, 5.6, N…
## $ r704dk4    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, 1, 1, NA, 1, NA, 1, 1, 1,…
## $ r704dk5    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, NA, 1, 2, NA, 2, NA, 2, 2, 2,…
## $ r704dk6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, 1, NA, 1, NA, 1, 1,…
## $ r704dk7    <dbl> 2, 3, 2, 3, 3, 3, 2, 2, 2, 2, NA, 2, 2, NA, 2, NA, 2, 2, 2,…
## $ r704ek2    <dbl> 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 4, 2, 1, 1, 0, 1, 1, 1, 1,…
## $ r704ek3    <dbl> 9.0, 2.0, NA, NA, 4.0, 8.0, 3.0, 4.0, NA, NA, NA, NA, NA, N…
## $ r704ek4    <dbl> 1, 1, NA, NA, 1, 1, 1, 1, NA, NA, NA, NA, NA, NA, NA, 1, NA…
## $ r704ek5    <dbl> 2, 2, NA, NA, 2, 2, 2, 2, NA, NA, NA, NA, NA, NA, NA, 2, NA…
## $ r704ek6    <dbl> 2, 1, NA, NA, 1, 1, 1, 2, NA, NA, NA, NA, NA, NA, NA, 1, NA…
## $ r704ek7    <dbl> 2, 1, NA, NA, 1, 2, 1, 1, NA, NA, NA, NA, NA, NA, NA, 2, NA…
## $ r704fk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r704fk3    <dbl> 99.8, 50.0, 99.8, 30.0, 26.0, 20.0, 99.8, 99.8, 6.9, 13.0, …
## $ r704fk4    <dbl> 2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1,…
## $ r704fk5    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2,…
## $ r704fk6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, 1, NA, 1, 1, 1, 1, …
## $ r704fk7    <dbl> 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r704gk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,…
## $ r704gk3    <dbl> 41.0, 50.0, 28.0, 30.0, 26.0, 20.0, 39.0, 37.0, 4.1, NA, 6.…
## $ r704gk4    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, 1, 1, 1, 2, 1, NA, 1, 1, 1, …
## $ r704gk5    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, NA, 1, 1, 2, 1, 2, NA, 2, 2, 2, …
## $ r704gk6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, 1, NA, 1, NA, 1, 1,…
## $ r704gk7    <dbl> 2, 3, 2, 3, 3, 3, 2, 2, 2, NA, 2, 2, 2, 2, 2, NA, 2, 1, 2, …
## $ r704hk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r704hk3    <dbl> 99.8, 99.8, 99.8, 99.8, 99.8, 99.8, 99.8, 99.8, 99.9, 99.9,…
## $ r704hk4    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2,…
## $ r704hk5    <dbl> 2, 1, 2, 1, 1, 1, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r704hk6    <dbl> 2, NA, 2, NA, NA, NA, 2, 2, 2, 2, 2, NA, 2, 2, 2, 2, 2, 2, …
## $ r704hk7    <dbl> 3, 4, 3, 4, 4, 4, 3, 3, 4, 4, 4, 2, 4, 4, 4, 4, 4, 4, 2, 4,…
## $ r704ik2    <dbl> 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 2, 2, 1, 0, 1, 1, 1,…
## $ r704ik3    <dbl> 2.0, 19.0, 1.0, 30.0, 26.0, 20.0, NA, NA, 4.3, 1.8, 3.5, NA…
## $ r704ik4    <dbl> 1, 1, 1, 1, 1, 1, NA, NA, 1, 1, 1, NA, 1, NA, NA, NA, 1, NA…
## $ r704ik5    <dbl> 2, 2, 2, 2, 2, 2, NA, NA, 1, 1, 1, NA, 2, NA, NA, NA, 2, NA…
## $ r704ik6    <dbl> 2, 2, 1, 2, 2, 2, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, 1,…
## $ r704ik7    <dbl> 2, 3, 1, 3, 3, 3, NA, NA, 2, 2, 2, NA, 2, NA, NA, NA, 2, NA…
## $ r704jk2    <dbl> 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 2, 1, 1, 0, 1, 0, 1, 0, 1,…
## $ r704jk3    <dbl> NA, 1.0, 1.0, 2.0, NA, NA, NA, NA, NA, NA, 1.5, NA, NA, NA,…
## $ r704jk4    <dbl> NA, 1, 1, 1, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, 1, NA, …
## $ r704jk5    <dbl> NA, 2, 2, 2, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, 2, NA, …
## $ r704jk6    <dbl> NA, 1, 1, 1, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA,…
## $ r704jk7    <dbl> NA, 1, 1, 1, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, 2, NA, …
## $ r704kk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r704kk3    <dbl> 41.0, 99.8, 23.0, 99.8, 99.8, 99.8, 39.0, 37.0, 61.9, 56.2,…
## $ r704kk4    <dbl> 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r704kk5    <dbl> 2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r704kk6    <dbl> 2, NA, 2, NA, NA, NA, 2, 2, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r704kk7    <dbl> 2, 4, 2, 4, 4, 4, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,…
## $ r704lk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,…
## $ r704lk3    <dbl> 41.0, 50.0, 28.0, 30.0, 26.0, 20.0, 39.0, 37.0, 5.6, NA, NA…
## $ r704lk4    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, NA, NA, 1, 1, 2, NA, 1, 1, 1, 1,…
## $ r704lk5    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, NA, NA, 1, 2, 1, NA, 2, 2, 2, 2,…
## $ r704lk6    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, NA, NA, NA, NA, 1, NA, NA, 1, 1, 1,…
## $ r704lk7    <dbl> 2, 3, 2, 3, 3, 3, 2, 2, 2, NA, NA, 2, 2, 2, NA, 2, 2, 2, 2,…
## $ r704mk2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,…
## $ r704mk3    <dbl> 41.0, 99.8, 28.0, 99.8, 99.8, 99.8, 39.0, 37.0, 6.8, NA, 2.…
## $ r704mk4    <dbl> 1, 2, 1, 2, 2, 2, 1, 1, 1, NA, 1, 1, 1, 2, NA, 1, 1, 1, 1, …
## $ r704mk5    <dbl> 2, 1, 2, 1, 1, 1, 2, 2, 1, NA, 1, 1, 2, 1, NA, 2, 2, 2, 2, …
## $ r704mk6    <dbl> 2, NA, 2, NA, NA, NA, 2, 2, NA, NA, NA, NA, 1, NA, NA, 1, 1…
## $ r704mk7    <dbl> 2, 4, 2, 4, 4, 4, 2, 2, 2, NA, 2, 2, 2, 2, NA, 2, 2, 2, 2, …
## $ r705a      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 14, 12, 16, 13, 24, 16, 12, 16, 0, …
## $ r705b      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 14, 12, 16, 13, 24, 16, 12, 16, 15,…
## $ r705c      <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r705d      <dbl> 0, 0, 1, 0, 0, 0, 0, 0, 15, 2, 0, 1, 6, 1, 1, 6, 1, 0, 0, 0…
## $ r706a1     <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0,…
## $ r706a2     <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r706b      <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r706c      <dbl> 0, 2, 0, 1, 1, 0, 1, 1, 0, 1, 0, 2, 1, 2, 2, 4, 1, 3, 1, 1,…
## $ r706d      <dbl> 1, 6, 3, 5, 2, 1, 1, 0, 1, 2, 3, 1, 2, 7, 6, 5, 4, 3, 5, 5,…
## $ r707       <dbl> 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2,…
## $ r708       <dbl> 0, 0, 0, 5, 0, 2, 0, 0, 0, 3, 0, 1, 0, 2, 1, 6, 3, 0, 1, 1,…
## $ r709ak2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r709ak3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709ak4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709bk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r709bk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709bk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709ck2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r709ck3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709ck4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709dk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r709dk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709dk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709ek2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r709ek3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709ek4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709fk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r709fk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709fk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709gk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r709gk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709gk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709hk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r709hk3    <dbl> NA, NA, NA, NA, NA, NA, NA, 1, 25, 98, 8, 15, 5, 5, 27, 36,…
## $ r709hk4    <dbl> NA, NA, NA, NA, NA, NA, NA, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0…
## $ r709ik2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r709ik3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709ik4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709jk2    <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r709jk3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r709jk4    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r710       <dbl> 0, 0, 0, 0, 2, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r711       <dbl> 13, 30, 50, 300, 100, 44, 20, 25, 127, 171, 80, 50, 156, 40…
## $ D_R.x      <chr> "", "", "", "", "", "", "", "", "", "", "", "", "", "", "",…
## $ r101.x     <chr> "11", "11", "11", "11", "11", "11", "11", "11", "34", "34",…
## $ r101n.x    <chr> "Aceh", "Aceh", "Aceh", "Aceh", "Aceh", "Aceh", "Aceh", "Ac…
## $ r102.x     <chr> "01", "01", "01", "01", "01", "01", "01", "01", "01", "01",…
## $ r102n.x    <chr> "Simeulue", "Simeulue", "Simeulue", "Simeulue", "Simeulue",…
## $ r103.x     <chr> "010", "010", "010", "010", "010", "010", "010", "010", "07…
## $ r103n.x    <chr> "Teupah Selatan", "Teupah Selatan", "Teupah Selatan", "Teup…
## $ r104.x     <chr> "001", "002", "003", "004", "005", "006", "007", "008", "00…
## $ r104n.x    <chr> "Latiung", "Labuhan Bajau", "Suak Lamatan", "Ana Ao", "Lata…
## $ r105.x     <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r805a      <dbl> 0, 0, 1, 2, 0, 0, 0, 0, 13, 3, 6, 6, 16, 5, 18, 11, 6, 2, 2…
## $ r805b      <dbl> 0, 0, 0, 2, 2, 1, 0, 0, 8, 6, 0, 7, 0, 0, 6, 6, 0, 9, 1, 5,…
## $ r805c      <dbl> 0, 0, 2, 1, 0, 1, 0, 0, 2, 2, 0, 5, 0, 1, 4, 0, 0, 4, 0, 1,…
## $ r805d      <dbl> 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 2, 23, 3, 22, 15, 6, 9, 4,…
## $ r805e      <dbl> 0, 0, 0, 11, 0, 1, 1, 0, 11, 21, 17, 2, 25, 3, 15, 31, 17, …
## $ r805f      <dbl> 0, 1, 3, 2, 3, 2, 0, 2, 13, 6, 10, 3, 52, 4, 10, 11, 28, 3,…
## $ r805g      <dbl> 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 31, 4, 0, 0, 5, 3, 2, 5, 0, 0…
## $ r805h      <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r805i      <dbl> 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 1, 0, 0, 0, 0, 3, 0, 0, 6,…
## $ r806       <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r807a      <dbl> 3, 3, 2, 3, 3, 3, 3, 3, 1, 1, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3,…
## $ r807b1     <dbl> NA, NA, 1, NA, NA, NA, NA, NA, 1, 1, 1, NA, NA, NA, NA, NA,…
## $ r807b2     <dbl> NA, NA, 2, NA, NA, NA, NA, NA, 2, 2, 2, NA, NA, NA, NA, NA,…
## $ r808a      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r808b      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r809a      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 14, 1, 17, 13, 1, 1, 13, 16, 18, 14…
## $ r809b      <dbl> 1, 0, 1, 1, 0, 1, 1, 1, 14, 11, 17, 9, 1, 1, 13, 16, 18, 14…
## $ r809c      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,…
## $ r809d      <dbl> 1, 1, 1, 1, 1, 1, 3, 4, 41, 23, 34, 13, 9, 38, 12, 16, 23, …
## $ r809e      <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 8, 1, 5, 1, 1, 1, 0, 1, 3, 2, 3, 13…
## $ r809f      <dbl> 0, 0, 8, 0, 0, 0, 1, 0, 2, 0, 3, 1, 1, 3, 0, 0, 1, 0, 0, 0,…
## $ r1001a     <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1001b1    <dbl> 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1001b2    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1001c1    <dbl> 3, 3, 3, 3, 3, 3, 3, 3, 1, 2, 2, 1, 3, 2, 2, 3, 3, 3, 3, 3,…
## $ r1001c2    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 1, 2, 2, 2, NA, 1, 1, NA, N…
## $ r1001c3    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, 2, 2, 1, 2, NA, 2, 2, NA, N…
## $ r1003a     <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r1003b     <dbl> 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1,…
## $ r1004      <dbl> 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2,…
## $ r1005a     <dbl> 0, 0, 0, 0, 0, 0, 1, 0, 1, 2, 0, 0, 0, 0, 5, 0, 1, 0, 3, 0,…
## $ r1005b     <dbl> 1, 1, 1, 1, 0, 0, 1, 1, 4, 5, 5, 4, 4, 3, 5, 5, 5, 5, 5, 5,…
## $ r1005c     <dbl> 3, 3, 2, 3, 4, 4, 2, 2, 3, 2, 2, 2, 3, 3, 2, 2, 3, 3, 1, 1,…
## $ r1005d     <dbl> 1, 1, 1, 2, NA, NA, 1, 1, 2, 2, 2, 1, 3, 2, 1, 1, 1, 1, 1, …
## $ r1006a     <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1006b     <dbl> 4, 4, 4, 4, 4, 4, 1, 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1007a     <dbl> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 4, 1, 4, 4, 4, 4,…
## $ r1007b     <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1007c     <dbl> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 1, 4, 4, 4, 1, 4, 4, 4, 4, 4,…
## $ r1008ak2   <dbl> 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1008bk2   <dbl> 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1008ck2   <dbl> 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1008dk2   <dbl> 1, 2, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 1,…
## $ r1008ek2   <dbl> 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1008fk2   <dbl> 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1008gk2   <dbl> 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1202a     <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 2, 0, 0, 0, 0, 0, 0, 0,…
## $ r1205a1    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 1, 1, 0, 0, 0, 0,…
## $ r1205a2    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r1205a3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,…
## $ r1206a3    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 1, 0, 0, 1, 0, 0, 0, 0, 0,…
## $ r1206a4    <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 4, 0, 0, 0, 0, 0, 0, 0,…
## $ r1207ak2   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r1207bk2   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0,…
## $ r1207ck2   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 1, 0, 2, 3, 1, 0, 0, 1, 1,…
## $ r1207dk2   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r1207ek2   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 1, 2, 0, 0, 1, 0, 0, 0, 1, 0,…
## $ r1207fk2   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1,…
## $ r1207gk2   <dbl> 1, 0, 1, 0, 0, 20, 1, 1, 15, 21, 6, 19, 3, 7, 8, 19, 14, 8,…
## $ r1207hk2   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r1207ik2   <dbl> 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r1207jk2   <dbl> 2, 0, 8, 0, 0, 0, 5, 6, 60, 61, 21, 25, 45, 28, 132, 60, 24…
## $ r1208a     <dbl> 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1,…
## $ r1208b     <dbl> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4,…
## $ r1208c     <dbl> 6, 6, 6, 6, 6, 6, 6, 6, 5, 6, 6, 5, 6, 5, 6, 6, 6, 6, 5, 6,…
## $ r1208d     <dbl> 8, 8, 8, 8, 8, 8, 8, 8, 7, 7, 8, 7, 7, 7, 7, 7, 7, 7, 7, 7,…
## $ r1209ak2   <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2,…
## $ r1209bk2   <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1209ck2   <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 1, 1, 2, 1, 2, 2,…
## $ r1209dk2   <dbl> 2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1209ek2   <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 1, 1,…
## $ r1209fk2   <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2,…
## $ r1209gk2   <dbl> 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1301a     <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1301b1k2  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r1301b2k2  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r1301b3k2  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r1301b4k2  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r1301b5k2  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r1301b6k2  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r1301b7k2  <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r1303a01k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2,…
## $ r1303a02k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1303a03k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1303a04k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1303a05k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1303a06k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1303a07k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2,…
## $ r1303a08k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1303a09k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2,…
## $ r1303a10k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1303a11k3 <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1305      <dbl> 2, 2, 3, 2, 2, 2, 3, 3, 40, 60, 65, 45, 63, 52, 50, 56, 57,…
## $ r1306a     <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2,…
## $ r1306b1    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1, NA, NA, NA, NA, …
## $ r1306c1    <dbl> 11.0, 3.0, 23.0, 7.0, 11.0, 18.0, 13.0, 15.0, 5.3, 3.0, NA,…
## $ r1307ak2   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r1307ak3   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ r1307bk2   <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r1307bk3   <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ r1308a     <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1308b     <dbl> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,…
## $ r1401a     <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1402a     <dbl> 3, 1, 1, 1, 1, 1, 2, 4, 2, 1, 1, 2, 3, 3, 1, 2, 1, 1, 2, 1,…
## $ r1402b     <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1402c     <dbl> 3, 3, 4, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,…
## $ r1402d     <dbl> 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 6, 5, 6, 5, 6, 6, 6, 5, 5,…
## $ r1402e     <dbl> 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7,…
## $ r1402f     <dbl> 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1402g     <dbl> 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 3, 4, 3, 4, 4, 4, 4, 4, 4, 3,…
## $ r1402h     <dbl> 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 6, 6, 5, 6, 6, 5, 6, 6,…
## $ r1402i     <dbl> 7, 7, 8, 7, 8, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 7,…
## $ r1404a     <dbl> 1, 1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2,…
## $ r1404b     <dbl> 3, 4, 4, 4, 4, 3, 3, 3, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4,…
## $ r1405      <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1406a     <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 1,…
## $ r1501ak2   <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1501ak3   <dbl> 15, 36, 56, 53, 48, 33, 27, 33, 145, 129, NA, 168, 182, 134…
## $ r1501ak4   <dbl> 1800000, 300000, 600000, 300, 300, 300000, 1800000, 1800000…
## $ r1501ak5   <dbl> 5, 25, 30, 0, 25, 25, 25, 30, 18, 6, NA, 22, 24, 8, 19, 19,…
## $ r1501bk2   <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1,…
## $ r1501bk3   <dbl> 15, 36, 56, 53, 55, 33, 27, 33, 197, 110, 132, NA, 82, NA, …
## $ r1501bk4   <dbl> 9e+05, 3e+05, 3e+05, 3e+02, 3e+02, 3e+05, 9e+05, 9e+05, 3e+…
## $ r1501bk5   <dbl> 2, 25, 30, 0, 25, 25, 12, 15, 12, 2, 18, NA, 5, NA, 10, 9, …
## $ r1501ck2   <dbl> 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2,…
## $ r1501ck3   <dbl> 72, 30, 40, NA, 35, 30, 83, 120, 230, 60, 71, NA, 160, 134,…
## $ r1501ck5   <dbl> 2, 30, 0, NA, 30, 40, 20, 20, 45, 23, 8, NA, 12, 8, 5, 5, 1…
## $ r1502_1    <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1502_1a   <dbl> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,…
## $ r1502_1b   <dbl> 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 5, 6, 6, 5, 5, 5, 5, 5, 5,…
## $ r1502_1c   <dbl> 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 7, 7, 7, 7,…
## $ r1502_1d   <dbl> 2, 2, 1, 2, 2, 2, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1502_2    <dbl> 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4,…
## $ r1502_3    <dbl> 6, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 5, 6, 5, 5, 5, 5, 5, 6, 6,…
## $ r1502_4    <dbl> 7, 8, 8, 8, 8, 8, 7, 7, 8, 8, 8, 7, 7, 7, 7, 7, 7, 7, 7, 7,…
## $ r1502_5    <dbl> 2, 2, 1, 2, 2, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 1, 2, 1,…
## $ r1502_6    <dbl> 3, 3, 3, 4, 4, 4, 3, 3, 4, 3, 4, 3, 3, 4, 3, 3, 3, 3, 3, 3,…
## $ r1502_7    <dbl> 6, 6, 6, 6, 6, 6, 5, 5, 6, 6, 6, 5, 5, 6, 5, 5, 5, 5, 5, 5,…
## $ r1502_8    <dbl> 7, 8, 8, 8, 8, 8, 7, 7, 8, 8, 8, 7, 7, 8, 7, 7, 7, 7, 7, 7,…
## $ r1502_9    <dbl> 1, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1502_10   <dbl> 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 3, 3, 4, 4, 4,…
## $ r1502_11   <dbl> 5, 6, 5, 6, 6, 6, 5, 5, 5, 6, 6, 5, 5, 5, 5, 5, 5, 5, 6, 5,…
## $ r1601ak2   <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 2, 2, 1, 1,…
## $ r1601bk2   <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1602a     <dbl> 4, 4, 3, 4, 4, 4, 4, 4, 3, 2, 2, 3, 4, 5, 5, 5, 6, 5, 5, 3,…
## $ r1602b     <dbl> 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 7, 3, 3, 6, 6, 6, 6, 3, 5,…
## $ r1602c     <dbl> 2, 2, 2, 4, 3, 3, 3, 3, 96, 99, 99, 69, 99, 99, 37, 99, 52,…
## $ r1602d     <dbl> 9, 12, 21, 14, 13, 13, 7, 8, 48, 64, 71, 45, 66, 52, 3, 59,…
## $ r1603a     <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ r1603c     <dbl> 5, 15, 6, 6, 15, 11, 12, 10, 7, 6, 5, 25, 9, 4, 8, 6, 4, 6,…

# --- Library ---
library(dplyr)

# --- Buat kode_kab ---
Podes21_all <- Podes21_all %>%
  mutate(
    kode_kab = paste0(r101, r102)
  )

# --- Filter hanya Pulau Sulawesi (r101 diawali '7') ---
Podes_sulawesi <- Podes21_all %>%
  filter(grepl("^7", r101))

# --- Agregasi per kabupaten/kota ---
# --- Agregasi per kabupaten/kota ---
Podes_kab <- Podes_sulawesi %>%
  group_by(kode_kab) %>%
  summarise(
    n_desa = n(),  # banyaknya desa dalam kabupaten/kota
    x1  = sum(r1501ak3, na.rm = TRUE),
    x2  = sum(ifelse(r1501ak3 == 5, 1, 0), na.rm = TRUE),
    x3  = sum(r711, na.rm = TRUE),
    x4  = sum(r501b, na.rm = TRUE),
    x5  = sum(r512b1, na.rm = TRUE),
    x6  = sum(r701dk2, r701dk3, r701ek2, r701ek3, r701lk2, r701lk3, na.rm = TRUE),
    x7  = sum(r701fk2, r701fk3, r701gk2, r701gk3, r701mk2, r701mk3, na.rm = TRUE),
    x8  = sum(r701hk2, r701hk3, r701ik2, r701ik3, r701jk2, r701jk3,
              r701nk2, r701nk3, na.rm = TRUE),
    
    # --- x9 & x10 diperbaiki sesuai definisi ---
    x9  = (sum(ifelse(r1005a == 0, 1, 0), na.rm = TRUE) / n_desa)*100,
    x10 = (sum(ifelse(r1005d == 1, 1, 0), na.rm = TRUE) / n_desa)*100,
    
    x11 = sum(r706a1, r706a2, r706b, r706c, r706d, na.rm = TRUE),
    x13 = sum(r1207ak2, r1207bk2, r1207ck2, r1207dk2, r1207ek2,
              r1207fk2, r1207gk2, r1207hk2, r1207ik2, r1207jk2,
              na.rm = TRUE)
  ) %>%
  ungroup()


# --- Cek hasil ---
glimpse(Podes_kab)

## Rows: 81
## Columns: 14
## $ kode_kab <chr> "7101", "7102", "7103", "7104", "7105", "7106", "7107", "7108…
## $ n_desa   <int> 202, 270, 167, 153, 178, 131, 107, 93, 144, 81, 81, 87, 69, 4…
## $ x1       <dbl> 21060, 21059, 11892, 8424, 17237, 13177, 11235, 2653, 3765, 3…
## $ x2       <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
## $ x3       <dbl> 7346, 11182, 5399, 4867, 7326, 2811, 5224, 2180, 1642, 3268, …
## $ x4       <dbl> 55, 63, 1242, 183, 60, 252, 48, 102, 73, 38, 30, 107, 70, 180…
## $ x5       <dbl> 7, 11, 0, 0, 3, 1, 4, 0, 2, 0, 1, 70, 21, 8, 3, 3, 16, 6, 1, …
## $ x6       <dbl> 237, 353, 226, 118, 245, 205, 104, 104, 102, 77, 61, 285, 122…
## $ x7       <dbl> 79, 109, 71, 46, 89, 80, 29, 26, 47, 28, 28, 107, 44, 25, 19,…
## $ x8       <dbl> 41, 58, 35, 34, 38, 44, 15, 11, 20, 13, 15, 97, 34, 19, 21, 4…
## $ x9       <dbl> 64.35644, 56.66667, 77.84431, 81.69935, 61.79775, 34.35115, 7…
## $ x10      <dbl> 76.23762, 94.07407, 83.23353, 71.24183, 90.44944, 83.96947, 8…
## $ x11      <dbl> 637, 1762, 666, 567, 648, 802, 455, 406, 507, 281, 208, 1146,…
## $ x13      <dbl> 4881, 6544, 2798, 2224, 4508, 4070, 1864, 1631, 2734, 1611, 1…

Korelasi dengan variabel Dependent

library(dplyr)

# --- Pastikan tipe data kode_kab sama di kedua data ---
Podes_kab <- Podes_kab %>%
  mutate(kode_kab = as.character(kode_kab))

hasil_proporsi <- hasil_proporsi %>%
  mutate(kode_kab = as.character(kode_kab))

# --- Gabungkan berdasarkan kode_kab ---
gabung_data <- left_join(Podes_kab, hasil_proporsi, by = "kode_kab")

# --- Hitung korelasi antara setiap x dan proporsi kawin dini ---
# Pilih hanya kolom x1:x13 dan proporsi_kawin_dini
data_korelasi <- gabung_data %>%
  select(starts_with("x"), proporsi_kawin_dini)

# Buat vektor hasil korelasi
hasil_cor <- sapply(data_korelasi %>% select(starts_with("x")),
                    function(x) cor(x, data_korelasi$proporsi_kawin_dini, use = "complete.obs"))

# --- Ubah jadi data frame yang rapi ---
hasil_cor_df <- data.frame(
  variabel = names(hasil_cor),
  korelasi = as.numeric(hasil_cor)
) %>%
  arrange(desc(abs(korelasi)))  # urutkan berdasar kekuatan korelasi

# --- Tampilkan hasil ---
print(hasil_cor_df)

##    variabel   korelasi
## 1        x9  0.4660767
## 2       x10 -0.3116552
## 3       x13 -0.2590530
## 4        x5 -0.2480425
## 5        x8 -0.2285251
## 6        x2  0.2235984
## 7       x11 -0.1823203
## 8        x3 -0.1741763
## 9        x1  0.1652257
## 10       x4  0.1466453
## 11       x6 -0.1214485
## 12       x7 -0.1135615

library(ggplot2)

# --- Visualisasi korelasi ---
ggplot(hasil_cor_df, aes(x = reorder(variabel, korelasi), y = korelasi, fill = korelasi)) +
  geom_col(show.legend = FALSE) +
  coord_flip() +
  scale_fill_gradient2(low = "#D73027", mid = "white", high = "#1A9850", midpoint = 0) +
  geom_text(aes(label = round(korelasi, 2)), hjust = ifelse(hasil_cor_df$korelasi > 0, -0.2, 1.2), size = 4) +
  theme_minimal(base_size = 13) +
  labs(
    title = "Korelasi antara Variabel Podes dan Proporsi Kawin Dini per Kabupaten/Kota",
    x = "Variabel Podes (x1–x13)",
    y = "Koefisien Korelasi Pearson"
  ) +
  theme(
    plot.title = element_text(face = "bold", hjust = 0.5),
    panel.grid.minor = element_blank()
  ) +
  ylim(min(hasil_cor_df$korelasi) - 0.05, max(hasil_cor_df$korelasi) + 0.05)

library(GGally)

## Registered S3 method overwritten by 'GGally':
##   method from   
##   +.gg   ggplot2

library(ggplot2)
library(dplyr)

# --- Ambil hanya variabel x dan proporsi kawin dini ---
data_plot <- gabung_data %>%
  select(starts_with("x"), proporsi_kawin_dini)

# --- Buat scatterplot matrix ---
ggpairs(
  data_plot,
  columns = 1:(ncol(data_plot) ),
  upper = list(continuous = wrap("cor", size = 3)),
  lower = list(continuous = wrap("points", alpha = 0.6, size = 1.5)),
  diag = list(continuous = wrap("densityDiag")),
  title = "Matriks Scatter Plot: Variabel Podes vs Proporsi Kawin Dini"
) +
  theme_bw(base_size = 10)

MODEL HB–BETA (tanpa error)

library(saeHB.ME.beta)
library(saeHB)

## 
## Attaching package: 'saeHB'

## The following object is masked from 'package:stats':
## 
##     Gamma

library(coda)

# Gunakan data dari package saeHB.ME.beta agar identik
dataBeta <- dataHBMEbeta
head(dataBeta)

##           Y        x1        x2        x3         x4       vardir      v.x1
## 1 1.0000000 0.2875775 0.6180179 0.4925665 0.78394648 4.517806e-04 0.2228771
## 2 1.0000000 0.7883051 0.3722381 0.6973738 0.19337868 2.689821e-04 0.4604680
## 3 1.0000000 0.4089769 0.5298357 0.6414624 0.01776581 3.941678e-05 0.5346108
## 4 0.9990303 0.8830174 0.8746823 0.6439229 0.40660787 1.896286e-02 0.8945672
## 5 1.0000000 0.9404673 0.5817501 0.9778534 0.48316767 3.602302e-03 1.3511417
## 6 1.0000000 0.0455565 0.8397678 0.4147353 0.42184495 2.745088e-04 0.3228122
##       v.x2
## 1 1.521402
## 2 5.593300
## 3 3.459347
## 4 2.375630
## 5 2.257685
## 6 4.060938

# Jalankan model Hierarchical Bayes dengan sebaran Beta
model_HB_beta <- Beta(
  formula = Y ~ x1 + x2,
  iter.update = 3,     # jumlah update MCMC
  iter.mcmc = 2000,    # jumlah iterasi total
  thin = 1,            # thinning
  burn.in = 1000,      # burn-in
  data = dataBeta
)

## Compiling model graph
##    Resolving undeclared variables
##    Allocating nodes
## Graph information:
##    Observed stochastic nodes: 30
##    Unobserved stochastic nodes: 66
##    Total graph size: 414
## 
## Initializing model
## 
## Compiling model graph
##    Resolving undeclared variables
##    Allocating nodes
## Graph information:
##    Observed stochastic nodes: 30
##    Unobserved stochastic nodes: 66
##    Total graph size: 414
## 
## Initializing model
## 
## Compiling model graph
##    Resolving undeclared variables
##    Allocating nodes
## Graph information:
##    Observed stochastic nodes: 30
##    Unobserved stochastic nodes: 66
##    Total graph size: 414
## 
## Initializing model

# Lihat hasil model HB–Beta
model_HB_beta$Est          # Estimasi mean (EBLUP Bayes)

##             MEAN         SD      2.5%       25%       50%       75%     97.5%
## mu[1]  0.8417642 0.07598925 0.6613228 0.8041597 0.8566971 0.8945428 0.9428540
## mu[2]  0.8484703 0.07358801 0.6641112 0.8081045 0.8635747 0.9012268 0.9521231
## mu[3]  0.8453542 0.07437769 0.6629852 0.8074508 0.8568588 0.8985891 0.9529790
## mu[4]  0.8643836 0.06862310 0.6975791 0.8286822 0.8762602 0.9144574 0.9613581
## mu[5]  0.8595546 0.07077234 0.6914296 0.8220387 0.8722676 0.9117747 0.9585147
## mu[6]  0.8489986 0.07729300 0.6537880 0.8075251 0.8656207 0.9066284 0.9528712
## mu[7]  0.7823427 0.09259892 0.5600467 0.7299045 0.7974732 0.8503109 0.9205174
## mu[8]  0.8696718 0.06849576 0.7014801 0.8344726 0.8823461 0.9171808 0.9643191
## mu[9]  0.8370508 0.07300443 0.6622725 0.7978534 0.8494049 0.8873093 0.9468506
## mu[10] 0.8566982 0.06928947 0.6911307 0.8204499 0.8721996 0.9052063 0.9578950
## mu[11] 0.8532113 0.07226238 0.6705391 0.8194574 0.8637081 0.9040477 0.9576305
## mu[12] 0.8250173 0.07774439 0.6296864 0.7809973 0.8386966 0.8806405 0.9377657
## mu[13] 0.8482801 0.07774654 0.6527416 0.8097682 0.8641906 0.9022840 0.9571817
## mu[14] 0.8342559 0.08705920 0.6300626 0.7859209 0.8518858 0.8970845 0.9526606
## mu[15] 0.8560106 0.07752828 0.6759063 0.8194884 0.8734872 0.9108043 0.9553293
## mu[16] 0.8472676 0.07809170 0.6602573 0.8113410 0.8610966 0.9026002 0.9518418
## mu[17] 0.7502260 0.11838968 0.4258025 0.6939007 0.7699627 0.8334617 0.9133651
## mu[18] 0.8582435 0.07641374 0.6750084 0.8176856 0.8738295 0.9166651 0.9573865
## mu[19] 0.8590749 0.06883832 0.6913094 0.8228490 0.8728385 0.9086824 0.9543235
## mu[20] 0.8734587 0.07280019 0.6794733 0.8411407 0.8882049 0.9236936 0.9655900
## mu[21] 0.8580096 0.06829880 0.6965702 0.8213201 0.8688314 0.9075889 0.9579718
## mu[22] 0.8115280 0.08885995 0.6104704 0.7584969 0.8276073 0.8773175 0.9382691
## mu[23] 0.8619894 0.07116302 0.6775220 0.8295270 0.8745942 0.9122365 0.9561166
## mu[24] 0.8140353 0.08953521 0.6094285 0.7590373 0.8287824 0.8809595 0.9453667
## mu[25] 0.8536248 0.07503719 0.6582056 0.8168286 0.8682172 0.9081541 0.9556421
## mu[26] 0.8192399 0.08296252 0.6158290 0.7734408 0.8320955 0.8817848 0.9445818
## mu[27] 0.8267838 0.09464301 0.6051763 0.7789638 0.8464083 0.8945566 0.9533073
## mu[28] 0.8498845 0.07185714 0.6825904 0.8153209 0.8606934 0.9013858 0.9497753
## mu[29] 0.8009558 0.09061633 0.5988682 0.7532376 0.8131689 0.8626044 0.9401017
## mu[30] 0.8281216 0.08274473 0.6380320 0.7797811 0.8424280 0.8885475 0.9501125

model_HB_beta$sd           # Simpangan baku penduga

## NULL

model_HB_beta$refVar       # Varians random effect antar-area

## [1] 0.3105044

model_HB_beta$coefficient  # Koefisien regresi (β)

##           Mean        SD       2.5%        25%       50%       75%    97.5%
## b[0] 1.2865061 0.3238299  0.6238373 1.08732249 1.2832419 1.4980746 1.926251
## b[1] 0.3079085 0.3964363 -0.4464257 0.04688665 0.3041073 0.5801215 1.053785
## b[2] 0.5737103 0.4689317 -0.2990102 0.25451131 0.5981241 0.8989685 1.446820

# Visualisasi MCMC
plot(model_HB_beta$plot[[3]])           # Trace dan density
autocorr.plot(model_HB_beta$plot[[3]])  # ACF (autokorelasi)

MODEL HB–BETA dengan Measurement Error

library(saeHB.ME.beta)
library(coda)

# Muat dataset simulasi yang sama (30 area)
data(dataHBMEbeta)
head(dataHBMEbeta)

##           Y        x1        x2        x3         x4       vardir      v.x1
## 1 1.0000000 0.2875775 0.6180179 0.4925665 0.78394648 4.517806e-04 0.2228771
## 2 1.0000000 0.7883051 0.3722381 0.6973738 0.19337868 2.689821e-04 0.4604680
## 3 1.0000000 0.4089769 0.5298357 0.6414624 0.01776581 3.941678e-05 0.5346108
## 4 0.9990303 0.8830174 0.8746823 0.6439229 0.40660787 1.896286e-02 0.8945672
## 5 1.0000000 0.9404673 0.5817501 0.9778534 0.48316767 3.602302e-03 1.3511417
## 6 1.0000000 0.0455565 0.8397678 0.4147353 0.42184495 2.745088e-04 0.3228122
##       v.x2
## 1 1.521402
## 2 5.593300
## 3 3.459347
## 4 2.375630
## 5 2.257685
## 6 4.060938

# Jalankan model HB–Beta dengan error pengukuran pada x1 dan x2
model_HB_ME_Beta <- meHBbeta(
  formula = Y ~ x1 + x2 + x3 + x4,        # model regresi area
  var.x = c("v.x1", "v.x2"),              # variabel bantu yang mengandung error
  iter.update = 3,                        # jumlah update chain
  iter.mcmc = 10000,                      # jumlah iterasi MCMC
  thin = 2,                               # thinning rate
  burn.in = 2000,                         # burn-in
  data = dataHBMEbeta
)

## Compiling model graph
##    Resolving undeclared variables
##    Allocating nodes
## Graph information:
##    Observed stochastic nodes: 30
##    Unobserved stochastic nodes: 128
##    Total graph size: 781
## 
## Initializing model
## 
## Compiling model graph
##    Resolving undeclared variables
##    Allocating nodes
## Graph information:
##    Observed stochastic nodes: 30
##    Unobserved stochastic nodes: 128
##    Total graph size: 781
## 
## Initializing model
## 
## Compiling model graph
##    Resolving undeclared variables
##    Allocating nodes
## Graph information:
##    Observed stochastic nodes: 30
##    Unobserved stochastic nodes: 128
##    Total graph size: 781
## 
## Initializing model

# Hasil model HB–Beta dengan Measurement Error
model_HB_ME_Beta$Est           # Estimasi proporsi hasil model

##             mean         sd      2.5%       25%       50%       75%     97.5%
## mu[1]  0.8601298 0.07533624 0.6707667 0.8216921 0.8746710 0.9151019 0.9606196
## mu[2]  0.8474379 0.08370795 0.6420314 0.8042749 0.8643090 0.9085285 0.9604077
## mu[3]  0.8340770 0.08660206 0.6300268 0.7886995 0.8499558 0.8972640 0.9549685
## mu[4]  0.8349424 0.08611277 0.6221212 0.7904305 0.8520659 0.8973842 0.9535799
## mu[5]  0.8811785 0.07331779 0.6919069 0.8488003 0.8982090 0.9323808 0.9708787
## mu[6]  0.8366367 0.08318499 0.6315791 0.7917020 0.8517386 0.8973500 0.9532399
## mu[7]  0.7043106 0.13884734 0.3847432 0.6177519 0.7273107 0.8095013 0.9129211
## mu[8]  0.8669272 0.07469426 0.6796311 0.8310854 0.8836205 0.9210844 0.9639800
## mu[9]  0.8257605 0.09174760 0.6015845 0.7766719 0.8424369 0.8939277 0.9541715
## mu[10] 0.8484652 0.07932907 0.6498650 0.8077446 0.8643695 0.9055831 0.9556742
## mu[11] 0.8620825 0.07692315 0.6709168 0.8224880 0.8779901 0.9184118 0.9651243
## mu[12] 0.8860272 0.07023050 0.7072921 0.8536545 0.9015772 0.9359952 0.9732577
## mu[13] 0.8242496 0.09087939 0.6041164 0.7773923 0.8410442 0.8891218 0.9528912
## mu[14] 0.7561718 0.11050843 0.5009905 0.6930745 0.7740915 0.8382382 0.9178883
## mu[15] 0.8774859 0.07338306 0.6877725 0.8431124 0.8950369 0.9295285 0.9691030
## mu[16] 0.8249788 0.09081562 0.6036540 0.7775971 0.8420319 0.8909089 0.9514479
## mu[17] 0.8339055 0.10755418 0.5528002 0.7835120 0.8594667 0.9124853 0.9648935
## mu[18] 0.8438058 0.08728520 0.6223316 0.8036991 0.8619206 0.9056239 0.9585253
## mu[19] 0.8515297 0.07917902 0.6537775 0.8105083 0.8682917 0.9090863 0.9584822
## mu[20] 0.8467927 0.08416252 0.6327447 0.8030573 0.8633022 0.9087624 0.9595601
## mu[21] 0.8963889 0.06741242 0.7226523 0.8666656 0.9124662 0.9437332 0.9764234
## mu[22] 0.8060277 0.10300432 0.5600550 0.7512002 0.8252829 0.8818878 0.9498324
## mu[23] 0.8309859 0.08971568 0.6059276 0.7845993 0.8476116 0.8957415 0.9550951
## mu[24] 0.7667520 0.11072154 0.5022903 0.7038320 0.7835006 0.8494611 0.9277656
## mu[25] 0.8582354 0.08010887 0.6514381 0.8190521 0.8758871 0.9163176 0.9614811
## mu[26] 0.8262386 0.09294337 0.5952682 0.7788170 0.8422277 0.8942712 0.9516807
## mu[27] 0.7197474 0.12878548 0.4279295 0.6396685 0.7402194 0.8152126 0.9117893
## mu[28] 0.8851535 0.06949801 0.7071462 0.8525937 0.9013202 0.9342023 0.9715028
## mu[29] 0.7961624 0.10889560 0.5339054 0.7382248 0.8173257 0.8763818 0.9440967
## mu[30] 0.8193921 0.11148425 0.5418154 0.7656392 0.8422937 0.9000979 0.9637994

model_HB_ME_Beta$coefficient   # Koefisien regresi (β)

##            Mean        SD       2.5%         25%        50%       75%     97.5%
## b[0] 1.07468671 0.3275393  0.4257869  0.85105733 1.07445737 1.2936883 1.7240299
## b[1] 0.03554304 0.2115482 -0.3649282 -0.10777289 0.03261345 0.1759827 0.4596355
## b[2] 0.01521104 0.1309057 -0.2415159 -0.07174256 0.01303860 0.1045060 0.2726201
## b[3] 0.75752504 0.4738123 -0.1756292  0.43107328 0.75406285 1.0788313 1.6722878
## b[4] 0.54095269 0.4233606 -0.2874948  0.25532810 0.54955840 0.8331090 1.3694609

model_HB_ME_Beta$refvar        # Varians efek area

## [1] 0.3241837

# Visualisasi MCMC
plot(model_HB_ME_Beta$plot[[3]])
autocorr.plot(model_HB_ME_Beta$plot[[3]])

Perbandingan Ringkas

# --- Ambil hasil estimasi utama (kolom mean) ---
hb_beta_est <- model_HB_beta$Est$MEAN
hb_me_beta_est <- model_HB_ME_Beta$Est$mean

# Pastikan jumlah area sama
n <- min(length(hb_beta_est), length(hb_me_beta_est))

# Buat tabel perbandingan
compare_est <- data.frame(
  Area = 1:n,
  HB_Beta = hb_beta_est[1:n],
  HB_ME_Beta = hb_me_beta_est[1:n],
  Selisih = hb_me_beta_est[1:n] - hb_beta_est[1:n]
)

# --- Tampilkan ringkasan hasil ---
head(compare_est)

##   Area   HB_Beta HB_ME_Beta      Selisih
## 1    1 0.8417642  0.8601298  0.018365677
## 2    2 0.8484703  0.8474379 -0.001032359
## 3    3 0.8453542  0.8340770 -0.011277188
## 4    4 0.8643836  0.8349424 -0.029441247
## 5    5 0.8595546  0.8811785  0.021623891
## 6    6 0.8489986  0.8366367 -0.012361875

summary(compare_est$Selisih)

##      Min.   1st Qu.    Median      Mean   3rd Qu.      Max. 
## -0.107036 -0.023595 -0.007889 -0.007718  0.008403  0.083679

# --- Plot perbandingan antar model ---
plot(compare_est$HB_Beta, compare_est$HB_ME_Beta,
     main = "Perbandingan Estimasi Proporsi: HB–Beta vs HB–Beta (ME)",
     xlab = "HB–Beta (tanpa Measurement Error)",
     ylab = "HB–Beta dengan Measurement Error",
     pch = 19, col = "blue", cex = 1.2)
abline(0, 1, col = "red", lwd = 2, lty = 2)
text(0.8, 0.6, "Garis merah = hasil identik", col = "red")

# --- Analisis tambahan ---
cat("\nKorelasi antar hasil dua model:\n")

## 
## Korelasi antar hasil dua model:

print(cor(compare_est$HB_Beta, compare_est$HB_ME_Beta))

## [1] 0.5339325

cat("\nRata-rata perbedaan (HB_ME_Beta - HB_Beta):\n")

## 
## Rata-rata perbedaan (HB_ME_Beta - HB_Beta):

print(mean(compare_est$Selisih))

## [1] -0.007717613