Performance of K-Means Clustering Algorithm in enriching a new concept of Amenities into Dwipa Ontology III within the Indonesia Tourism Domain
Guson Prasamuarso Kuntarto, Shania Isyahrani, Irwan Prasetya Gunawan · 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) · 2019
Responding to the development of Tourism in Indonesia, Ontology DWIPA III was built to represent the tourism domain in Indonesia, especially in the Regency of Bali that consists of Class/subclass Accommodation, Attraction, Regency and Event. Tourism consist of 3 main elements, namely Attraction, Accessibility and Amenity. Related to this, Ontology DWIPA III still has shortcomings in the Amenity concept that represent the tourism domain. This research uses the Ontology Enrichment methodology to add new concepts to the existing DWIPA ontology. The sources of the data are scraped from TripAdvisor web. Amenity data that has been collected is given a feature to differentiate the amenities, and the features is determined by its weighted using the Terms Frequency Inverse Document Frequency method. The process continues by Classifying the data using K-Means Algorithm. The final results of this study indicate that DWIPA Ontology was successfully enriched by having 4 main Classes, 29 subclasses and 319 instances.