Text Mining of Customer Reviews in the Hotel Industry Conducted a text mining analysis using R Studio to identify the key service attributes that influence customer satisfaction in the hotel industry. I collected and analyzed customer reviews of hotels to understand the aspects of hotel services that customers frequently mention and value. The analysis involved cleaning and preprocessing the review data, including removing stop words, punctuation, and irrelevant terms, followed by text mining and frequency analysis to identify recurring words and themes. Based on the customer reviews, I identified important service attributes such as cleanliness, room quality, staff behaviour, location, food quality, service, comfort, and value for money. The project helped translate unstructured customer feedback into meaningful insights, providing an understanding of customer expectations and the service factors that can be prioritized by hotels to improve the overall customer experience.

JK=jenis kelamin TP=tingkat pendidikan

4X2 DAN 2X2

Nama : Aliefia Novita Putri NIM : 2507016063

Matriks korelasi dan contoh tabel kontingensi

Ulfa Ayudia Putri (2507016057)

Nama: Sofi Fakidhotul Mutafida NIM: 2507016014 Kelas: A

Nama : Kholifatussania NIM : 2507016062 Mata kuliah : Komputasi Statistika Dosen Pengampu : Dr. M. Fathurahman, S.Si, M.Si Sumber: Buku Belajar Statistika dengan R