IndonesiAPIs: Access Indonesian Data via Public APIs and Curated Datasets • IndonesiAPIs

library(IndonesiAPIs)
library(ggplot2)
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

Introduction

The IndonesiAPIs package provides a unified interface to access open data from the World Bank API, Nager.Date API, and the REST Countries API, with a focus on Indonesia. It allows users to retrieve up-to-date or historical information on topics such as economic indicators, population statistics, national holidays, and basic geopolitical details.

In addition to API-access functions, the package includes a curated collection of open datasets related to Indonesia. These datasets cover a wide range of topics including consumer prices, poverty probability, food prices by region, tourism destinations, and minimum wage statistics.

IndonesiAPIs is designed to support users working with data related to Indonesia by integrating international RESTful APIs with structured and reliable datasets from public, academic, and governmental sources into a single, easy-to-use R package.

Functions for IndonesiAPIs

The IndonesiAPIs package provides several core functions to access real-time and structured information about Indonesia from public APIs such as the World Bank API, Nager.Date, and the REST Countries API. Below is a list of the main functions included in the package:

get_indonesia_child_mortality(): Get Under-5 Mortality Rate in Indonesia from World Bank
get_indonesia_cpi(): Get Indonesia’s Consumer Price Index from World Bank
get_indonesia_energy_use(): Get Indonesia’s Energy Use (kg of oil equivalent per capita) from World Bank
get_indonesia_gdp(): Get Indonesia’s GDP (Current US$) from World Bank
get_indonesia_holidays(): Get official public holidays in Indonesia for a given year, e.g. get_indonesia_holidays(2025)
get_indonesia_hospital_beds(): Get Hospital Beds per 1,000 People in Indonesia from World Bank
get_indonesia_life_expectancy(): Get Indonesia’s Life Expectancy at Birth from World Bank
get_indonesia_literacy_rate(): Get Indonesia’s Literacy Rate (Age 15+) from World Bank
get_indonesia_population(): Get Indonesia’s Total Population from World Bank
get_indonesia_unemployment(): Get Indonesia’s Unemployment Rate from World Bank
get_country_info_idn(): Get Key Country Information About Indonesia from the REST Countries API
view_datasets_IndonesiAPIs(): View Available Datasets in IndonesiAPIs

These functions allow users to access high-quality and structured information on Indonesia, which can be combined with tools like dplyr and ggplot2 to support a wide range of data analysis, visualization, and research tasks. In the following sections, you’ll find examples on how to work with IndonesiAPIs in practical scenarios.

Indonesia’s GDP (Current US$) from World Bank 2022 - 2017



indonesia_gdp <- head(get_indonesia_gdp())

print(indonesia_gdp)
#> # A tibble: 6 × 5
#>   indicator         country    year   value value_label      
#>   <chr>             <chr>     <int>   <dbl> <chr>            
#> 1 GDP (current US$) Indonesia  2022 1.32e12 1,319,101,183,380
#> 2 GDP (current US$) Indonesia  2021 1.19e12 1,186,509,691,087
#> 3 GDP (current US$) Indonesia  2020 1.06e12 1,059,054,842,698
#> 4 GDP (current US$) Indonesia  2019 1.12e12 1,119,099,871,350
#> 5 GDP (current US$) Indonesia  2018 1.04e12 1,042,271,532,989
#> 6 GDP (current US$) Indonesia  2017 1.02e12 1,015,618,744,160

Indonesia’s Life Expectancy at Birth from World Bank 2022 - 2017


indonesia_life_expectancy <- head(get_indonesia_life_expectancy())

print(indonesia_life_expectancy)
#> # A tibble: 6 × 4
#>   indicator                               country    year value
#>   <chr>                                   <chr>     <int> <dbl>
#> 1 Life expectancy at birth, total (years) Indonesia  2022  70.9
#> 2 Life expectancy at birth, total (years) Indonesia  2021  67.5
#> 3 Life expectancy at birth, total (years) Indonesia  2020  68.8
#> 4 Life expectancy at birth, total (years) Indonesia  2019  70.3
#> 5 Life expectancy at birth, total (years) Indonesia  2018  70.1
#> 6 Life expectancy at birth, total (years) Indonesia  2017  70.0

Indonesia’s Total Population from World Bank 2022 - 2017


indonesia_population <- head(get_indonesia_population())

print(indonesia_population)
#> # A tibble: 6 × 5
#>   indicator         country    year     value value_label
#>   <chr>             <chr>     <int>     <int> <chr>      
#> 1 Population, total Indonesia  2022 278830529 278,830,529
#> 2 Population, total Indonesia  2021 276758053 276,758,053
#> 3 Population, total Indonesia  2020 274814866 274,814,866
#> 4 Population, total Indonesia  2019 272489381 272,489,381
#> 5 Population, total Indonesia  2018 269951846 269,951,846
#> 6 Population, total Indonesia  2017 267346658 267,346,658

Top 10 Regions with Highest Average Minimum Wage (2015-2023)



# Bar chart with better formatted x-axis
indonesia_minwage_tbl_df %>%
  filter(YEAR >= 2015) %>%
  group_by(REGION) %>%
  summarise(avg_salary = mean(SALARY, na.rm = TRUE), .groups = 'drop') %>%
  arrange(desc(avg_salary)) %>%
  slice_head(n = 10) %>%
  ggplot(aes(x = reorder(REGION, avg_salary), y = avg_salary)) +
  geom_col(fill = "steelblue", alpha = 0.8) +
  coord_flip() +
  scale_y_continuous(
    labels = function(x) format(x, big.mark = ",", scientific = FALSE)
  ) +
  labs(
    title = "Top 10 Regions with Highest Average Minimum Wage (2015-2023)",
    subtitle = "Indonesian Minimum Wage by Region",
    x = "Region",
    y = "Average Minimum Wage (IDR)",
    caption = "Source: IndonesiAPIs package"
  ) +
  theme_minimal() +
  theme(
    plot.title = element_text(size = 14, face = "bold"),
    plot.subtitle = element_text(size = 12),
    axis.text = element_text(size = 10),
    axis.title = element_text(size = 11)
  )

Dataset Suffixes

Each dataset in IndonesiAPIs is labeled with a suffix to indicate its structure and type:

_df: A standard data frame.
_tbl_df: A tibble data frame object.

Datasets Included in IndonesiAPIs

In addition to API access functions, IndonesiAPIs offers a curated collection of open datasets focused on Indonesia. These preloaded datasets cover a wide range of topics including consumer prices, poverty probability, food prices by region, tourism destinations, and minimum wage statistics. Below are some featured examples:

Bali_tbl_df: A tibble containing food price data in Bali, Indonesia.
indonesia_minwage_tbl_df: A tibble containing monthly minimum wage or Upah Minimum Regional (UMR) data in Indonesian Rupiah (IDR) across various regions of Indonesia from 1997 to 2025.
DKIJakarta_tbl_df: A tibble containing food price data in DKI Jakarta, Indonesia.

Conclusion

The IndonesiAPIs package offers a unified interface for accessing both real-time data from public APIs and a curated collection of datasets about Indonesia. Covering a wide spectrum of topics from economic indicators, holidays, and demographic statistics via international APIs, to detailed datasets on consumer prices, poverty probability, food prices by region, tourism destinations, and minimum wage statistics, IndonesiAPIs provides users with reliable, structured, and high-quality data.

Designed to support reproducible research, education, and data journalism, the package empowers users to analyze and visualize Indonesia-focused data directly within R, using tidy formats and well-documented sources.