Penerapan Machine Learning Untuk Menentukan Tingkat Kepuasan Tamu Hotel Dymens Menggunakan Metode Vader - Agung Ramadhanu; Muhammad Raihan Zaky; Mokti Isra; Neni Sri Wahyuni Nengsih; Sularno Sularno (Prodi Sistem Informasi Universitas Dharma Andalas, 2023)
In Indonesia there are several social media that provide reviews and experiences related to an inn, including Tripadvisor.com, Traveloka, Tiket.com, and many more. Over time, machine learning can replace and improve human abilities in various fields, Machine Learning has been extensively researched and used to solve various problems. Among them is to find out how the assessment and views of hotel guests regarding the services and policies set. With reviews from customers or hotel guests, we can find out how the quality of the product or service is implemented, so that an evaluation can be carried out to increase customer satisfaction. Sentiment analysis, or opinion evaluation is an active area of ​​study in the field of natural language processing that analyzes opinions, sentiments, evaluations, attitudes, and emotions through improving the processing of subjectivity in texts. Sentiment analysis is useful for a wide variety of issues of interest to human-computer interaction practices and researchers, as well as people from fields such as: sociology, marketing and advertising, psychology, eco-economics, and political science. The process of sentiment analysis is often done to find out positive, neutral or negative opinion from the public regarding a certain matter. The Valence Aware Dictionary and Sentiment Reasoner (VADER) method is a sentiment analysis method that can identify a person's emotions based on words. So that the VADER Method can be used to identify hotel guest reviews and hotel management can make decisions based on the results of these assessments or reviews