Online Motor Vehicle Sales Data for Supporting Policy in Manufacturing Sector
Satria Bagus Panuntun, Khairunnisah, Dewi Krismawati, Setia Pramana · 2021
Data and information on the income of the large and medium trade and the manufacturing sector are essential for the government to make policies. Currently, official statistics containing this information are still carried out conventionally. There has to be a new data source that can be used as a faster and more granular alternative reference. The goal of this research is to investigate a novel technique to generate data on vehicle sales in Indonesia from big data that can support and provide an overview of the manufacturing sector in real-time and may be used as a comparative or complementary to official statistics. This research uses a web scraping method from one of the largest vehicle advertiser sites in Indonesia. Vehicle sales data is collected weekly for the four vehicle types advertised in Indonesia using the HTML structure of the site. The Python programming language's Scrapy module is implemented. Data collection is carried out every week, and 358,451 vehicle advertisements have been collected from January 2019 to June 2021. The findings suggest that vehicle sales data from big data can be used as a comparative or complementary to official statistics, as well as supporting data in the manufacturing sector. By using web scraping techniques, indicators that usually require more time and cost can be done in real-time at a lower budget. This new approach is expected to improve the quality of official statistics in the manufacturing sector.