Claim Missing Document
Check
Articles

Found 12 Documents
Search

Pemanfaatan Digital Marketing Dan Pengembangan SDM untuk Meningkatan Kualitas Pelayanan Akomodasi di Desa Wisata Taro Tegallalang Gianyar Bali Kalpikawati, Ida Ayu; Sulistyawati, Ni Luh Ketut Sri; Pinaria, Ni Wayan Chintia; Adinda, Clearesta; Suastini, Ni Made; Loananta, Cahyo Purnomo; Pratiwi, Kadek Andita Dwi; Jata, I Ketut
Jurnal Pengabdian Kepada Masyarakat Makardhi Vol. 4 No. 2 (2024): Jurnal Pengabdian Kepada Masyarakat MAKARDHI
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat Politeknik Pariwisata Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52352/makardhi.v4i2.1588

Abstract

Taro Village is one of the leading tourist villages in Gianyar, Bali, offering natural and cultural potential that supports community welfare through tourism. By 2024, there has been a significant increase in the number of accommodations in Taro Village, which has created new challenges regarding digital marketing and meeting service standards in accommodation management. This Community Service Program aims to enhance the competence of accommodation managers in Taro Village through training on excellent service, accommodation standardization, and effective digital marketing. The program combines socialization and practical activities, focusing on improving accommodation visibility as well as implementing service standards and processes. The expected outcomes include enhanced competence of accommodation managers, a deeper understanding of digital marketing, and better service standard implementation, enabling Taro Village to compete as a premier tourist destination. The program was attended by 30 participants, including accommodation owners, members of Pokdarwis, and local residents involved in the tourism sector in Taro Village. The activities, consisting of socialization and practical sessions, were held on September 17-18, 2024. The evaluation was conducted by distributing questionnaires to participants to measure their satisfaction. The results showed that the average satisfaction score reached 3.8, which falls into the "very good" category, with most participants expressing a willingness to participate in similar activities in the future. Participants also requested more practical materials so they can directly learn and apply the skills taught, making the training more relevant to their field needs.  
Analyzing TripAdvisor reviews to improve service quality at Courtyard Marriott Bali Nusa Dua Resort Vijaya, Bagaskara; Pitanatri, Putu Diah Sastri; Pratiwi, Kadek Andita Dwi
Annals of Management and Organization Research Vol. 7 No. 1 (2025): August
Publisher : goodwood publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/amor.v7i1.2857

Abstract

Purpose: This study aims to explore trends in guest satisfaction at the Courtyard by Marriott Bali Nusa Dua Resort by analyzing online reviews from TripAdvisor, with the objective of enhancing service quality. Methods: The research follows a systematic methodology that begins with scraping guest reviews from TripAdvisor, ensuring the collection of relevant data. Subsequently, a thorough data cleaning and preprocessing process is undertaken to guarantee high-quality data. The study then utilizes time series analysis, specifically the ARIMA model, to analyze the evolving patterns of guest satisfaction over time. Results/findings: The findings show that the majority of guest feedback is positive, indicating general satisfaction with the hotel. The ARIMA model reveals that guest satisfaction is highly influenced by previous satisfaction levels, suggesting a trend where past experiences strongly impact future perceptions. Conclusions: These results provide valuable insights into the key drivers of guest satisfaction, offering actionable recommendations for hotel management. By understanding the dynamic factors that influence guest experiences, management can improve service quality, respond more effectively to unexpected situations, and remain competitive in the market. Limitations: The ARIMA model does not account for external factors, such as holiday seasons or marketing changes, nor does it analyze the specific content of reviews or differentiate between guest segments. Additionally, comparisons with competitors can provide a broader strategic context for a more comprehensive understanding. Contribution: The combination of sentiment analysis and time series forecasting in this study offers a unique contribution, enabling data-driven decisions that support continuous service improvement and customer satisfaction.