Online price prediction system of consumption commodities

Growth of online shopping brings possibilities for research and study. We can use online price data for example, for forming consumer price index. This research proposes online price prediction system that use online price commodities from online retailers as data source. To collect many products information as consumption commodities from several online retailer, we use web scraping technique. Collecting consumption commodities from online stores is possible and well proven. We also find the acceptance of proposed system using Technology Acceptance Model (TAM) from user's perspective. The result show that this system can predict price of certain commodity close to the price data survey and 83,34% of respondents believe this system can be implemented as supported system or substituted of Online CPS System in the future.