factor described tourists who are h

factor described tourists who are highly interested in exploring different cultures and different way of lives, enjoy meeting people, and look for- ward to new challenges. The second factor was labeled ‘Shopaholic’, which explained 13.09% of the total variance, with a Cronbach's alpha value of 0.842. The second factor described tourists who spend a lot of money on shopping for goods when they visit a holiday destination. The third factor was labeled ‘Aspiring indulger’, which explained 8.96% of the total variance, with a Cronbach's alpha value of 0.741. The third factor described tourists who are ambitious and optimistic in facing life challenges. This type of tourist seeks comfort during their visit to a destination. The fourth factor was labeled ‘Conservative’, which ex- plained 6.69% of the total variance, with a Cronbach's alpha value of
0.742. The fourth factor described tourists who enjoy spending their leisure time at home or doing activities around the house. The fifth factor was labeled ‘Sport adventurous’, which explained 6.13% of the total variance, with a Cronbach's alpha value of 0.735. The fifth factor described tourists who enjoy sports and outdoor activities. The sixth factor was labeled ‘Foodie’, which explained 4.44% of the total variance, with a Cronbach's alpha value of 0.679. The sixth factor described tourists who enjoy a great variety of cuisine and like to dine out with friends.

4.3. Clusters of tourist lifestyles

A cluster analysis was applied to the six factors to classify tourists into mutually exclusive groups. The analysis was performed using a K-Means clustering procedure (Lee, Lee, Bernhard, & Yoon, 2006). Trials analyzing three, four, and five clusters were conducted, and the results were compared to identify the most appropriate number of clusters. Based on the results of the analyses for three to five clusters, the four-cluster solution appeared to be the most appropriate in terms of cluster interpretation, meaningfulness, and size. The mean value was used as the base for interpreting and naming the clusters. Mean values above
4.00 indicate that a tourist lifestyle attribute is important, while mean values below 4.00 indicate that the attribute has low importance (Konu, Laukkanen, & Komppula, 2011). As shown in Table 4, the 393 respondents were grouped into four clusters: Culture interest shopaholic (17.6%), Sporty culture explorer (15.8%), Aspiring vacationer (21.9%), and Want-everything vacationer (44.8%).

4.4. Discriminant analysis

A discriminant analysis was performed to validate the result of the cluster analysis. The analysis examined the differences among the four clusters and determined variables that differentiate these clusters. The analysis also calculated the degree to which respondents were correctly classified (Malhotra, 2010). Three canonical discriminant functions were calculated and found to be statistically significant. Function 1 explained 41% of the variance (eigenvalue = 1.471, Wilks' Lambda =
0.096, χ2 = 908.74, df = 15, Sig. = 0.000). Function 2 explained 30%
of the variance (eigenvalue = 1.074, Wilks' Lambda = 0.237, χ2 =
558.24, df = 8, Sig. = 0.000). Function 3 explained 29% of the variance (eigenvalue = 1.037, Wilks' Lambda = 0.491, χ2 = 275.63, df = 3, Sig. = 0.000). In total, 90.8% of the 393 grouped cases were correctly classified, which indicated a high accuracy rate and suggested that the four clusters were satisfactorily classified.

4.5. Demographic profiles within clusters

To better understand the demographic characteristics of the four clusters, chi-square tests for independence analysis were conducted on each cluster using the demographic profiles of the respondents. The results of the analysis (Table 5) showed that gender (χ2 = 1.785, p = 0.618) and travel arrangements (χ2 = 9.365, p = 0.155) had no significant relationship with the clusters. All four clusters were dominated by male foreign visitors, and foreign visitors within these clusters arranged their flight to Jakarta and their accommodations in Jakarta

Results (Indonesian) 1:

faktor dijelaskan wisatawan yang sangat tertarik dalam mengeksplorasi berbagai budaya dan cara yang berbeda dari kehidupan, menikmati bertemu orang-orang, dan melihat untuk bangsal untuk tantangan baru. Faktor kedua dicap 'Belanja', yang menjelaskan 13.09% dari total varians, dengan nilai alpha Cronbach 0.842. Faktor yang kedua digambarkan wisatawan yang menghabiskan banyak uang pada belanja barang ketika mereka mengunjungi tujuan wisata. Faktor ketiga dicap 'Aspiring indulger', yang menjelaskan 8.96% dari total varians, dengan nilai alpha Cronbach 0.741. Faktor ketiga dijelaskan wisatawan yang ambisius dan optimis dalam menghadapi tantangan hidup. Jenis wisata mencari kenyamanan selama kunjungan mereka ke tujuan. Faktor yang keempat adalah label 'Konservatif', yang ex - plained 6.69% dari total varians, dengan nilai alpha Cronbach0.742. faktor keempat dijelaskan wisatawan yang menikmati menghabiskan waktu senggang mereka di rumah atau melakukan kegiatan di sekitar rumah. Faktor fifth dicap 'Sport petualang', yang menjelaskan 6.13% dari total varians, dengan nilai alpha Cronbach 0.735. Faktor fifth dijelaskan wisatawan yang menikmati olahraga dan kegiatan di luar ruangan. Faktor keenam dicap 'Foodie', yang menjelaskan 4.44% dari total varians, dengan nilai alpha Cronbach 0.679. Faktor keenam dijelaskan wisatawan yang menikmati berbagai macam masakan dan ingin makan di luar dengan teman-teman.4.3. kelompok Wisata gaya hidupAnalisa cluster diterapkan faktor enam untuk mengklasifikasikan wisatawan ke dalam kelompok saling eksklusif. Analisis dilakukan menggunakan K-berarti clustering prosedur (Lee, Lee, Bernhard, & Yoon, 2006). Uji menganalisis tiga, empat, dan kelompok-kelompok five dilakukan, dan hasil dibandingkan untuk mengidentifikasi paling sesuai jumlah kluster. Berdasarkan hasil analisis untuk tiga sampai five cluster, solusi empat-cluster yang muncul untuk menjadi yang paling tepat dalam hal penafsiran cluster, kebermaknaan, dan ukuran. Nilai rata-rata digunakan sebagai dasar untuk menafsirkan dan penamaan cluster. Nilai di atas4.00 menunjukkan bahwa atribut gaya hidup Wisata penting, sementara nilai-nilai yang berarti di bawah 4.00 menunjukkan bahwa atribut memiliki kepentingan rendah (Konu, Laukkanen, & Komppula, 2011). Seperti yang ditunjukkan dalam tabel 4, responden 393 dikelompokkan ke dalam empat kluster: budaya menarik shopaholic (17.6%), Sporty budaya explorer (15,8%), pelayanan Aspiring (21,9%), dan ingin-semuanya pelayanan (44,8%).4.4. diskriminan analisisDiskriminan analisis ini dilakukan untuk memvalidasi hasil analisa cluster. Analisis diperiksa perbedaan antara empat kluster dan ditentukan variabel yang membedakan kelompok ini. Analisis juga dihitung tingkat responden yang itu benar classified (Malhotra, 2010). Tiga fungsi diskriminan kanonik dihitung dan ditemukan untuk menjadi Statistik significant. Fungsi 1 menjelaskan 41% varians (nilai eigen = 1.471, Wilks' Lambda =0.096, χ2 = 908.74, df = 15, Sig. = 0.000). Fungsi 2 menjelaskan 30%varians (nilai eigen = 1.074, Wilks' Lambda = 0.237, χ2 =558.24, df = 8, Sig. = 0.000). Fungsi 3 menjelaskan 29% dari varians (nilai eigen = 1.037, Wilks' Lambda = 0.491, χ2 = 275.63, df = 3, Sig. = 0.000). Secara total, 90.8% dari kasus dikelompokkan 393 yang benar classified, yang menunjukkan tingkat akurasi yang tinggi dan menyarankan bahwa empat kluster yang memuaskan classified.4.5. demografis profiles dalam kelompokUntuk lebih memahami karakteristik demografis empat kluster, Chi-kuadrat tes untuk kemerdekaan analisis dilakukan di setiap cluster yang menggunakan profiles demografis responden. Hasil analisis (Tabel 5) menunjukkan bahwa jenis kelamin (χ2 = 1.785, p = 0.618) dan perjalanan (χ2 = 9.365, p = 0.155) tidak significant berhubungan dengan cluster. Semua empat kluster didominasi oleh laki-laki pengunjung asing, dan pengunjung asing dalam kelompok ini diatur mereka penerbangan untuk Jakarta dan akomodasi mereka di Jakarta