<![CDATA[This research aims to find out the right strategy based on an analysis of the dominant factors that determinetourists staying at the Puri Bagus Candidasa hotel. The problem of this research is to determine the factors thatdetermine tourists to stay at the Puri Bagus Candidasa hotel and to analyze the dominant factors determiningtourists' decisions to stay at the Puri Bagus Candidasa hotel. The sample was selected as many as 110respondents using purposive sampling technique. Data processing was carried out with SPSS software version23.0 for Windows. The principal component analysis (PCA) method produces four factors that determinetourists' decisions to stay at the Puri Bagus Candidasa Hotel, Karangasem Bali. These four factors areadvantages factors which consist of product factors, place factors, price factors and physical evidence factors.The second factor is the added value factor which consists of cultural factors, people factors and promotionfactors. The third factor is supporting factors which consist of social factors and process factors. The fourthfactor is personal factors and psychological factors. The dominant factor that determines tourists to stay at thePuri Bagus Candidasa hotel is the advantages factor with an eigenvalue of 2.235 and a variance percentagevalue of 20.316%. Companies are expected to continue to maintain product quality, comfort and safety at hotellocations as well as maintain the physical quality of the building. From the results of factor rotation, it wasfound that personal factors are the factors that have the lowest eigenvalue, where one of the indicators is thetourist's lifestyle, economy and psychology. This can trigger them to recommend the hotel to their relativeswho have the same lifestyle and economic situation. From the results of the analysis of respondentcharacteristics, it was found that the tourists who stayed overnight predominantly came from Germany, so itwas necessary to improve services for German tourists, for example by training staff to learn German.Keywords: Factor Analysis, Hotels, Tourist Decision]]>
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