Go to example tasks
Normalize Indonesian Customer Addresses
Created by
Devan Primadita
Parse messy Indonesian customer addresses into structured JSON with province, city/regency, district, village, street, RT/RW, postal code, landmarks, match level, and confidence. Built for AI agents, logistics, e-commerce, CRM, and automation.
Indonesia Address Parser & Normalizerdevan_ziho/indonesia-address-parser
Raw address
Normalized address
Street
House number
+13 fieldsTextNumberBooleanListObject
Input
Alamat Indonesia:Jl Sunan Kalijaga No 27 RT02 RW05 Kec Lowokwaru Kota Malang Jatim dekat Alfamart
Daftar Alamat Indonesia:Jl Kaliurang 25 Depok Sleman Jogja+4
Output fields
Raw address
Normalized address
Street
House number
RT
RW
Village / Kelurahan
District / Kecamatan
City / Regency
Province
Postal code
Landmark
Confidence
National match score
Match level
Region code
Warnings
Sign up on Apify01
Create your Apify account to access the Indonesia Address Parser & Normalizer.
Start the run02
The Actor will start running based on the input automatically.
Receive the output03
Monitor the progress in real-time. You will be notified as soon as your dataset is complete and ready for review.
Integrate into your workflow04
The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow.
