How to scrape logistics and supply chain data from Indonetwork using the Minexa.ai extension

Indonesia's logistics sector spans hundreds of verified freight forwarders, cargo agents, and supply chain operators, all listed publicly on Indonetwork (indonetwork.co.id). Getting that data into a spreadsheet manually is slow and error-prone. This guide shows how to extract it in minutes using the Minexa.ai Chrome extension, no code required.

https://www.youtube.com/watch?v=tcElG2F9t6M

Stage 1: Open the directory and launch the extension

Navigate to the Indonetwork cargo and logistics company directory at indonetwork.co.id/k/kargo-dan-logistik/perusahaan. Once the page loads, open Minexa.ai from your Chrome toolbar.

Click I'm on the right page inside the extension popup to confirm you are on the page you want to scrape. Minexa.ai will begin detecting the page structure automatically.

Stage 2: Confirm pagination

Minexa.ai detects the pagination method on the page automatically. You will see a summary of what it found, including which navigation control it identified. Review it and click Continue.

After confirming pagination, choose whether to scrape the listing page only or to also follow each company link and extract detail page data. For most logistics research tasks, the list page alone contains enough structured information.

Install the Minexa.ai extension

Stage 3: Select the data container

Minexa.ai highlights the repeating company card container on the page automatically. Confirm the selection and click Create scraper. The extension maps every data point it finds inside each card.

Once the scraper is created, you can browse all extracted columns using the next and previous navigation inside the extension panel.

What the extracted data looks like

Each company row in the output includes fields like these:

{
  "company_name": "Levy Bintang Logistik",
  "address": "Jl. Tongkol No. 2 RT 08, RW 04, Ancol, Jakarta Utara",
  "company_description": "Jasa ekspedisi door to door Jabodetabek...",
  "membership_badge_class": "membership-badge align-self-center align-middle ruby",
  "premium_membership_info": "Perusahaan ini adalah Perusahaan dengan keanggotaan Premium Ruby...",
  "years_joined": "Telah bergabung selama 1 Tahun",
  "company_link": "/company/levy-logistik"
}

The membership_badge_class field encodes the membership tier (ruby, gold, blue-onyx) directly in the CSS class string, so you can filter by tier programmatically without parsing any badge label text. The years_joined field gives a readable tenure string per company, useful for segmenting established operators from newer entrants. The two image fields, image_src and image_url, capture different loading states of the company logo, which helps downstream pipelines resolve the correct asset regardless of how the page rendered.

Stage 4: Run the job and export

After the scraper is saved, run the job from the Minexa.ai dashboard. Results appear in a live table as pages are processed.

Once complete, export to Excel or JSON in one click. You can also connect directly to Google Sheets or set the job on a recurring schedule from the summary screen.

The scraper you trained is reusable. Run it again any time to capture updated listings without repeating the setup.

Get started with Minexa.ai

For a related walkthrough covering catalogue data extraction without code, see: Scraping book listings for publishers: a structured guide to extracting catalogue data without code.