Analysis Of Customer Satisfaction Sentiment At Pharmacies Using The Naïve Bayes Method - Mufliha Mursalim; Andi Ircham Hidayat; Aulyah Zakilah Ifani (Inspiration: Jurnal Teknologi Informasi dan Komunikasi, 2025)
This study tries to find out how satisfied customers are with the services at Apotek MM Farma by using the Naive Bayes classification technique. The background of this study arose due to several obstacles experienced by customers, such as limited parking space, a manual cashier system, the absence of a comfortable waiting room, and inconsistent staff service. These things can affect customer satisfaction with the pharmacy as a whole. The data in this study were obtained from the results of questionnaires answered by 500 respondents. Each answer was categorized into three levels of satisfaction: satisfied, quite satisfied, and dissatisfied. The analysis process was carried out by separating attribute and target data, then the data was divided into 80% for Training data (400 data) and 20% for Test data (100 data). A classification model was built using the Naive Bayes algorithm to predict the level of satisfaction based on the available data. From the classification results, it was found that the majority of respondents (450 people) were satisfied, 44 people were quite satisfied, and only 6 people were Not satisfied. The model showed an accuracy level of 80%, with the "satisfied" category being the most accurately recognized. Meanwhile, the "quite satisfied" category still has low accuracy due to the small amount of data. In conclusion, the Naive Bayes method can be used to help pharmacies understand customer perceptions and improve service quality in a more targeted and efficient manner.