Postal Codes Dataset for Indonesia, ID

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Postal Codes Dataset for Indonesia, ID including name of the city, town, or place, various administrative divisions and alternative city names.

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Dataset Files

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/logistics/postal-codes-id/
https://datahub.io/logistics/postal-codes-id/_r/-/.licensing-notes.md
https://datahub.io/logistics/postal-codes-id/_r/-/README.md
https://datahub.io/logistics/postal-codes-id/_r/-/datapackage.yml
Key Files

Start with these files — they give you everything you need to understand and access the dataset.

datapackage.ymlmetadata & schema
https://datahub.io/logistics/postal-codes-id/_r/-/datapackage.yml
README.mddocumentation
https://datahub.io/logistics/postal-codes-id/_r/-/README.md
Typical Usage
  1. 1. Fetch datapackage.yml to inspect schema and resources
  2. 2. Download data resources listed in datapackage.yml
  3. 3. Read README.md for full context

Data Files

Postal Codes Data Resource for Indonesia, ID

About

Last updated
7 November 2024
Total rows
...
Format
CSV
File size
5.56 kB

About this dataset

Postal Codes Dataset for Indonesia (ID)

This dataset contains Indonesian kodepos — 81,044 rows covering all 8,266 postal codes, across all 38 provinces and all 514 regencies and cities.

Four administrative tiers, none collapsed. Indonesia's hierarchy is Provinsi → Kabupaten/Kota → Kecamatan → Desa/Kelurahan, and kodepos are assigned at the village tier. This schema carries all four: place_name is the village or urban ward, with district, regency and province in admin_name3 / admin_name2 / admin_name1.

Granularity note: a kodepos is not one-to-one with a village. Several villages routinely share one code, so a code legitimately appears on many rows. The primary key is (postal_code, admin_code3, place_name), never postal_code alone.

Administrative coverage: 69,338 rows (85.6%) carry the full four-tier hierarchy. The remaining 11,706 carry the postal facts — code, place name, coordinate — with the administrative columns blank, because the source's place name could not be matched to a unique entry in the official register. Those cells are blank rather than guessed: a wrong region is worse than an absent one. No postal code is lost this way — all 8,266 are present. Every row is all-or-nothing on the admin tiers; there are no half-filled hierarchies. Filter on a populated admin_name1 if you need fully-classified rows only.

Province codes are current. admin_code1 is the ISO 3166-2:ID code with the ID- prefix stripped, on the present 38-province structure — including the four provinces created in the 2022 Papua restructure: Papua Selatan (PS), Papua Tengah (PT), Papua Pegunungan (PE) and Papua Barat Daya (PD). Widely-circulated Indonesian postal extracts still carry the retired 34-province coding, in which 91 and 94 denote different provinces than they do today. Codes here are the current ones.

Coordinate accuracy: 8,320 rows have accuracy 1, meaning the point was interpolated by the source from neighbouring postal codes rather than matched to a gazetteer entry. Coordinates are not village-precise — many villages sharing a code share a single point. Check accuracy before relying on a coordinate.

Note: This dataset is a sample containing the first 100 rows. If you need access to the complete dataset, please contact our sales team for more information: datahub@datopian.com

Data Sources

Postal codes, place names and coordinates are sourced from GeoNames (CC BY 4.0), a community-maintained open geographic database.

The administrative hierarchy — province, regency/city and district names and codes — is taken from the Republic of Indonesia's Ministry of Home Affairs decree Kepmendagri No. 300.2.2-2430 Tahun 2025, Kode dan Data Wilayah Administrasi Pemerintahan, and joined onto the postal layer. Under UU No. 28 Tahun 2014 Pasal 42, Indonesian laws and regulations carry no copyright, so this layer is in the public domain.

Usage

The dataset files are available in CSV format and can be accessed and downloaded using the links provided in the datapackage.yml.

postal_code carries significant leading zeros and must be read as text (dtype=str), or use the schema in the packaged datapackage.json. The administrative codes admin_code2 and admin_code3 are dotted strings (11.01, 11.01.01) and must not be parsed as numbers.

For access to the full dataset or other inquiries, please contact our sales team at datahub@datopian.com