Analisis Sentimen Berbasis Aspek Ulasan Pelanggan Terhadap Kertanegara Premium Guest House Menggunakan Support Vector Machine - Wirdhayanti Paulina; Fitra Abdurrachman Bachtiar; Alfi Nur Rusydi (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2020)
Kertanegara Premium Guest House is one of the inns in the city of Malang, located on Jl. Semeru No.59. Kertanegara is very aware of the importance of the existence of E-WOM (Electronic Word Of Mouth) for the continuity of its business. E-WOM can be disseminated through customer reviews. Kertanegara has two sources of customer reviews namely Guest Reviews and online reviews on the OTA (Online Travel Agent) site. At present, the process of processing customer reviews is still focused only on Guest Review. But on the other hand, Kertanegara also has a review on the OTA website that needs to be processed because 90 percent of the booking process comes from the OTA website. One method that can be used to analyze and process the review text is sentiment analysis. Sentiment analysis is carried out at the aspect level to determine services and aspects that have negative or positive polarity using the Support Vector Machine (SVM) and Term Weighting (TF-IDF) methods. The review text data used in the Indonesian language comes from the sites of Agoda.com, Expedia, Pegi-Pegi, Booking.Com, TripAdvisor and has a timeline from 2012 to 2019. Testing the classification results produce an average Accuracy value above 70%. The results of the analysis are then visualized through a dashboard by displaying 6 important components so that it can assist Kertanegara in taking strategic steps to fix, improve and improve services that have negative polarity.