Menggali suara konsumen: analisis ulasan google maps untuk evaluasi layanan bisnis di indonesia
Abstract
The development of digital technology has transformed the way companies interact with customers, one of which is through location-based platforms such as Google Maps. In addition to functioning as a digital map, Google Maps allows users to provide reviews of products or services, which greatly influence public perception and potential customers’ decisions. These reviews can thus be utilized as an important data source for improving service quality and business strategies. However, collecting reviews manually is inefficient, time-consuming, and prone to errors, especially when the number of reviews is very large. To address this issue, this study develops a Google Maps Reviews Scraper, a Python-based system that automates the collection of review data. The system is equipped with a FastAPI backend and a CodeIgniter 4-based web interface, making it easy to use even for non-technical users. The scraped data is stored in Excel (.xlsx) format to facilitate further analysis. Experimental results show that the system operates reliably with an average speed of 1.8 reviews per second and can handle varying amounts of reviews without significant performance degradation. The integration of a simple interface makes the system practical, efficient, and ready to support data-driven decision-making based on customer feedback. Therefore, this research presents a solution that reduces the limitations of manual methods while enhancing business effectiveness in analyzing customer reviews.
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