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Pengaruh Pemasaran Konten Melalui Instagram @Rockbarbali Terhadap Minat Beli Tamu di Rock Bar Bali Noviari Wedanti, Dewa Ayu; Santi Diwyarthi, Ni Desak Made; Adinda, Clearesta
Jurnal Multidisiplin West Science Vol 3 No 10 (2024): Jurnal Multidisiplin West Science
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/jmws.v3i10.1654

Abstract

Penelitian ini bertujuan untuk mengetahui pengaruh firm generated content terhadap minat beli tamu, pengaruh electronic word of mouth terhadap minat beli tamu, serta pengaruh firm generated content dan electronic word of mouth secara simultan terhadap minat beli tamu di Rock Bar Bali. Data dikumpulkan melalui kuesioner yang disebarkan kepada pengikut akun Instagram Rock Bar dan dianalisis menggunakan SPSS versi 25. Teknik analisis data yang digunakan dalam penelitian ini adalah uji asumsi klasik, analisis regresi linear berganda, uji t, uji F, koefisien determinasi Hasil penelitian menunjukkan bahwa firm generated content dan electronic word of mouth secara signifikan dan positif mempengaruhi minat beli tamu. Kontribusi kedua variabel ini terhadap minat beli mencapai 73,5%. Temuan ini menunjukkan bahwa strategi marketing yang berfokus pada pembuatan konten berkualitas dan mendorong ulasan positif dari pengunjung dapat menjadi strategi yang efektif untuk meningkatkan minat beli tamu di Rock Bar Bali.
The role of seasonal trends in shaping tourist preferences for luxury resort: Big data approach Pamungkas, Luh Made Gunapria Hindu Rajeswari; Pitanatri, Putu Diah Sastri; Adinda, Clearesta
Journal of Sustainable Tourism and Entrepreneurship Vol. 7 No. 1 (2025): September
Publisher : Goodwood Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/joste.v7i1.2927

Abstract

Purpose: This study aims to examine seasonal patterns in tourist preferences for luxury resort stays in Bali, with a focus on how cultural backgrounds influence accommodation choices. The goal is to help resorts better understand guest behavior and optimize occupancy strategies. Methodology/approach: The research analyzes monthly online review data from Tripadvisor for Bvlgari Resort Bali, a prominent luxury hotel. A time-series analysis using the ARIMA (Autoregressive Integrated Moving Average) model is applied to forecast occupancy trends. Prior to modeling, the data is tested for stationarity. In addition to forecasting, the study explores guest preferences by analyzing cultural characteristics inferred from reviews, categorizing them into collectivist and individualist orientations. Results/findings: Findings reveal that occupancy trends do not strictly align with the hotel’s predefined seasonal categories. Instead, they are shaped by global travel trends and cultural factors. Guests from collectivist cultures tend to prefer facilities that support group interaction and shared experiences, while those from individualist cultures prioritize privacy, exclusivity, and personalized services. The ARIMA model delivers accurate forecasting results, helping to predict future occupancy rates effectively. Conclusion: IoT integration enhances the reliability of hospital-based PV systems. Tourist behavior is not solely dictated by conventional seasons but also by cultural expectations and travel motivations. Leveraging these insights allows hotels to better align operations, marketing, and pricing strategies with actual guest preferences. Limitations: The study is limited to a single resort and uses data from one online review platform, which may not fully capture the diversity of all guests. Contribution: This study contributes to tourism analytics, cross-cultural marketing, and hotel management by offering data-driven strategies to enhance occupancy performance.