James Adolf Paparang
Universitas Ekonomi Triatma Mulya, Badung

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FAKTOR-FAKTOR YANG DIPERTIMBANGKAN WISATAWAN MENGGUNAKAN JASA ONLINE BOOKING BERBASIS APLIKASI TRAVELOKA DI FAVE HOTEL KUTA KARTIKA PLAZA James Adolf Paparang; Luh Komang Candra Dewi
Journal Research of Management Vol. 1 No. 2 (2020): Journal Research of Management (JARMA)
Publisher : Universitas Triatma Mulya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (386.119 KB) | DOI: 10.51713/jarma.v1i2.21

Abstract

This study aims to determine what factors and which factors are the most dominant that tourist consider in using online booking service in the Traveloka application at Fave Hotel Kuta Kartika Plaza. The design of this study used quantitative descriptive analysis with SPSS version 24 analysis tool. This study used 85 respondents as the research sample drawn based on the purposive sampling method. The research method applied in this study is based on analysis of factor analysis with data collection techniques used are interviews, documentation, questionnaires. The results of this study show that only 16 independent variables can be analyzed further from a total of 17 independent variables. Of the 16 variables after the factor rotation process, there are five main components. Thenaming of new factors is determined according to the variables that make up the factor. The first factor is the company image factor that have the highest eigenvalue value of 5.558 and are able to explain the total variance of 34.756%. The second factor is marketing mix factor with an eigenvalue value of 2.520 with a variance percentage of 15,750%. The third is the brand factor with an eigenvalue value of2.400 with a total variance of 15.000%. The fourth socio cultural factor that has an eigenvalue of 1,823 with a total variance of 11,394%. The fifth factor is individual factor with an eigenvalue value of 1.304 which is able to explain the total variance of 8,147%. Implications for companies to always maintain service quality and also the quality of their applications, as well as to evaluate price, social and lifestylefactors that have small eigenvalue values compared to individual factors and service quality.