---
license: mit
task_categories:
- text-classification
- token-classification
tags:
- job-market
- scraping
- indonesia
- recruitment
pretty_name: Glints Indonesia Job Postings
size_categories:
- 1K<n<10K
language:
- id
- en
---

# Glints Job Scraper Dataset

## Description
This dataset provides a collection of job postings from [Glints Indonesia](https://glints.com), developed for the **Analitik Big Data** course to scrape job data from sites.
## Methodology
The data acquisition utilized a hybrid scraping approach:
* **API Reverse Engineering:** Request headers and GraphQL query structures were reverse-engineered to fetch structured data from unofficial endpoints.
* **Parsing:** [BeautifulSoup4](https://www.crummy.com/software/BeautifulSoup/) was used to extract metadata from HTML fields not fully serialized in the API.
* **Environment:** Developed using Python 3.12 within a dedicated virtual environment.

Note: This dataset contains multiple duplicate data as the jobs may fall into multiple job categories.

## Dataset Structure

The dataset consists of the following attributes:

| Attribute Name | Description | Example Value |
| :--- | :--- | :--- |
| `job_title` | The specific title or position of the job. | Data Analyst, Backend Engineer |
| `company_name` | The name of the hiring organization. | PT Tokopedia, Gojek |
| `location` | The city or work location. | Jakarta, Surabaya, Remote |
| `job_type` | The type of employment contract. | Full-time, Part-time, Internship |
| `experience_level` | The required level of professional experience. | Fresh Graduate, 2-3 tahun |
| `education_req` | Minimum educational background required. | S1 Informatika, D3 semua jurusan |
| `salary_range` | Reported compensation range (if available). | Rp 8.000.000 – Rp 12.000.000 |
| `job_requirements` | List of required technical and soft skills. | Python, SQL, komunikasi baik |
| `job_responsibilities` | Core tasks and responsibilities of the role. | Menganalisis data penjualan, ... |
| `posted_date` | The date the vacancy was originally posted. | 2024-11-15 |
| `source_platform` | The platform from which the data was scraped. | Glints |
| `category_scraped` | Broad job category or department. | IT, Admin HR |

## Use Cases
* **Classification:** Using `job_description` or `job_requirements` to predict `kategori`.
* **Salary Analysis:** Investigating how `experience_level` and `location` impact `salary_range`.
* **Named Entity Recognition (NER):** Extracting specific skills or tools from requirement texts.

---
**Disclaimer:** *This project is for educational purposes only. Users should respect the target platform's Terms of Service regarding data usage.*