Abstract

Amidst the fluctuations in computercomponent prices brought about by the Covid-19pandemic, a comprehensive analysis platform hasbeen developed to address this challenge. Thisinnovative platform harnesses historical datasourced from prominent e-commerce platforms suchas Shopee, Blibli, and Tokopedia, presenting userswith insightful average price graphs categorized bycomponent series and types. The researchmethodology adopted follows a prototype approach,encompassing meticulous phases ranging fromneeds analysis, application design, prototyping,testing, evaluation, prototype refinement, through toimplementation and ongoing maintenance. Thesuccessful implementation of this system, powered bythe Python programming language, features robustfunctionalities including product search anddynamic graphical representations derived fromhistorical data. The data retrieval process, utilizingthe Scraping method, occurs at regular intervals ona weekly basis. Upon meticulous analysis ofhistorical data spanning from January to July 2022,a noteworthy trend emerged, highlighting thatShopee and Tokopedia consistently offer computercomponents at relatively more affordable pricescompared to Blibli. The conclusive findings of thisresearch underscore the platform's efficacy inproviding an essential tool for users navigating thecomplex landscape of computer component pricedynamics, particularly in the unprecedented contextof the ongoing pandemic. This platform not onlyfacilitates monitoring but also empowers users withvaluable insights crucial for informed purchasingdecisions based on stable and budget-friendly pricingstructures.

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