Indonesia is one of the countries that have many scattered areas. One of the issues of the many scattered areas is the development of underdeveloped areas. Scientific research can be used as a reference for increasing the development of an area based on the frequency of an area being the object of research by representing the data represented in maps and statistics. A histogram map will help in the process of analyzing areas and topics that are not covered by the research. The data collection technique used is distributed parallel web scraping to speed up the collection process from 46,280 regions in Indonesia. The system development method used is the SDLC (Software Development Life Cycle) waterfall starting from requirements analysis, system design, development, testing, and maintenance. The results are that the distributed scraping process generates data faster than running a single scraper. Scraping result data will be processed into maps and statistics that can assist researchers in interpreting and figuring out underdeveloped areas in Indonesia.