Sentiment Analysis of Public Satisfaction Toward Banjar Grilled Chicken Restaurant Using Random Forest - Muhammad Raihan Ramandha Putra; Heny Pratiwi; Kusno Harianto (TEPIAN, 2026)
This study aims to explore the level of public satisfaction with the Banjar grilled chicken restaurant by utilizing customer reviews on the Google Maps platform. These reviews serve as a primary source of information that reflects public perceptions regarding the quality of food, service standards, pricing, and the overall atmosphere of the restaurant environment. In the digital era, online reviews have become an essential factor influencing consumer decisions, as many potential customers rely on shared experiences before visiting a restaurant. However, the large volume of reviews available on Google Maps makes manual analysis inefficient, impractical, and excessively time-consuming, especially when the data continues to grow over time. Therefore, this study adopts a text mining–based analytical approach combined with the Random Forest algorithm to automatically classify customer sentiment in a structured and systematic manner. The data used in this research consist of Indonesian-language comments collected from Google Maps, which are then categorized into two main sentiment classes: positive and negative. The research process involves several stages, including data collection, text preprocessing such as cleaning and normalization, word weighting using the TF-IDF method, and sentiment classification using the Random Forest algorithm, followed by model evaluation through a confusion matrix to measure performance accuracy. The final results are expected to provide a comprehensive overview of customer satisfaction levels and offer valuable insights that can assist restaurant management in improving service quality, enhancing customer experience, and developing more effective business strategies in the future.