Having a rapid growth across the world, Online Gig Economy (OGE) has the potential to reduce unemployment in Indonesia. It offers flexible working arrangement, flexible recruitment and new job types. Unfortunately, current existing economic and labor measurement systems are still not suitable to measure OGE distribution in Indonesia, especially for digital gig workers. The goal of this research is to portray Indonesian digital workers in OGE Platforms. This research relied on web crawling and web scraping for data collection combined with Automatic Text Classification (ATC) for data aggregation and classification. By delving nine platforms, 2,062 active gig workers were captured from 171,033 Indonesian users. Their profile was distributed into several dimensions: affiliated platforms, work fields, provinces, and paid salary. The result shows that most of gig workers were categorized in creative and multimedia. Considering IDR 3.4 million as the average of gig workers' paid salary, gig economy offer competitive and promising alternative for society to get money. These findings showed the significant role of internet to achieve better live and reduce unemployment.