Analisis Sentimen Ulasan Pelanggan Online Ubi Madu Cilembu Abah Nana Menggunakan Algoritma Naïve Bayes - Muhammad Rafly Al Fattah Zain; Mia Kamayani (STMIK Budi Darma, 2023)
This research aims to analyze the sentiment of online customer reviews for Ubi Madu Cilembu Abah Nana using the Naïve Bayes algorithm. The study has two main objectives: to classify the sentiment analysis of reviews into positive and negative categories regarding the service and products of Ubi Madu Cilembu Abah Nana, as well as to evaluate the accuracy level of the final classification results. The data was collected from online food delivery applications such as Gofood, Grabfood, and Shopeefood. The data used in this study amounts to 259 entries, with 310 positive and 49 negative data points. After conducting experiments, an accuracy result of 86.29% was obtained in Experiment 1 using the Split Data operator, and an accuracy of 86.12% was achieved in Experiment 2 utilizing Cross Validation with the assistance of language experts. The findings of this research indicate that the Naïve Bayes algorithm can be employed to classify customer sentiment towards the service and products of Ubi Madu Cilembu Abah Nana with a significantly high accuracy rate. These results can be valuable for Ubi Madu Cilembu Abah Nana in enhancing their service and product quality based on customer feedback. Additionally, this study also contributes to the field of sentiment analysis and natural language processing by applying classification algorithms to customer review data.