Abstract:In today's digital era, revitalizing the hospitality industry through technological innovation is crucial for enhancing competitiveness and improving customer experience. By gaining a deeper understanding of customer needs…
ds and developing service innovations, hotels can deliver more personalized and satisfying experiences. This shift in vision toward better customer service underscores the need for continued research on the paradigm shift within the hospitality sector. This study aims to observe and explore changes in the hospitality industry, with the goal of identifying paradigm evolutions and their contributions to service efficiency and quality. The research is expected to offer new insights into the dimensions of customer experience and internal operations that require rethinking, while also identifying cohesive strategies to integrate digital and physical elements. Furthermore, it analyzes the impact of hotel development control policies, management strategies, and technological innovations, thereby contributing both theoretically and practically to the development of the hospitality industry in Yogyakarta in response to the challenges of digital transformation.
Abstract:The rapid growth of the hotel industry requires hotels to improve operational planning, one of which is by forecasting room reservations. Inaccurate forecasting may cause an imbalance between room availability and customer…
er demand. This study aims to compare the Weighted Moving Average and Single Exponential Smoothing algorithms in forecasting room reservations at Raz Hotel and Convention Medan using historical data from January 2025 to May 2026. The research method consisted of data collection, forecasting using both algorithms, and accuracy evaluation through Mean Absolute Deviation, Mean Squared Error, and Mean Absolute Percentage Error. The results indicate that the Single Exponential Smoothing algorithm achieved a Mean Absolute Percentage Error of 15.24%, which is lower than the 15.63% obtained by the Weighted Moving Average algorithm. Furthermore, the Single Exponential Smoothing algorithm predicted 835.90 room reservations for June 2026. Therefore, it can be concluded that the Single Exponential Smoothing algorithm provides better forecasting accuracy and is more suitable for predicting room reservations at Raz Hotel and Convention Medan.
Abstract:The Covid-19 pandemic affected many sectors, including the hospitality, the businesses of travel, food and drink, and entertainment services. Even the future of tourism is seen with pessimism, particularly in places where…
e it is the main industry and where growth is planned. This may incentivize the travel and hospitality sector, particularly the hotel sector, to explore for strategies to weather the Covid-19 pandemic. This research uses a literature survey method. This method helps understand the relevance of new research and its relationship with previous research, identifying all previous scientific literature, including books, journal articles and theses, relating to the potential of the hotel business as a Staycation trend. This research aims to determine the potential of the hotel business as a Staycation trend. The research results show that 4-star and 3-star hotels differ in their understanding and application of the terms Daycation and Staycation, which mean a holiday of one day or a maximum of eight hours, however two out of five hotels still use the term Staycation even though the holiday is less than eight hours. During the pandemic, the term Staycation is also used. The findings indicate that it is important to maintain or improve hotel products and the use of digital marketing, especially social media, and continue to innovate to maintain a good image which relate to the prospects of the hotel business as a holiday style.
Rettobjaan, Vitalia Fina Carla, Yudha, Anak Agung Ngurah Bagus Arista, Bendesa, I Komang Gde, Wirajaya, Made Karma Maha, Savitri, Ni Luh Putu Ayu, Agustina, Febyola
Abstract:Badung Regency is one of the districts that has quite a lot of tourist areas and also business activities ranging from hotels, trade to MSMEs. Currently, technology and information develop and spread rapidly. Many people,…
, from parents to young people, have the opportunity to use digital media to promote tourism and MSME businesses. The aim of this activity is to increase people's ability to use digital media to promote tourism and improve their business by using social media. This activity was held at the Sangeh Village Perbekel Office, Badung Regency. This community service activity is aimed at the Krama Desa Adat, Yowana, and Pakis in Sangaeh Village, Badung Regency, which consists of 105 people. Counseling is provided through the method of activities carried out. The result is a society that is able to use social media well and wisely; they can use social media to show the various potentials of their traditional villages.
Keywords: business; promotion; social media.
Abstract:Abstract: Today, many users use online platforms rather than offline platforms for ticket bookings, involving a wide range of services such as flights, hotels, trains, buses, and entertainment. PegiPegi.com, as one of the…
e fastest growing online travel agencies in Indonesia, demonstrates success by understanding the value of technology and maintaining strong partnerships. Users of this platform often provide reviews, viewing user reviews can be done manually but this will have a less effective impact, so it needs to be done automatically with sentiment analysis. This research the Naïve Bayes method in sentiment analysis of PegiPegi.com reviews, with a focus on understanding customer satisfaction and service improvement. By combining these approaches, this research contributes to a deeper understanding of user responses to OTA services and presents the evaluation results of the Multinomial Naive Bayes classification model with an accuracy rate of 89.5%. The high precision in the Negative class demonstrates the model's ability to identify negative reviews. However, there are challenges in classifying the Neutral class, indicating the potential for further improvement. Nevertheless, the F1 score of 0.522 reflects a good balance between overall precision, recall so it can be concluded the naïve bayes algorithm is successful for performing sentiment analysis.
Keywords: Sentiment analysis; naïve bayes algorithm; pegipegi.com; playstore
Abstract: Saat ini banyak pengguna platform online dibandingkan offline untuk pemesanan tiket, yang melibatkan berbagai layanan seperti penerbangan, hotel, kereta api, bus, dan hiburan. PegiPegi.com, sebagai salah satu agen perjalanan online yang berkembang pesat di Indonesia, menunjukkan keberhasilan dengan memahami nilai teknologi dan mempertahankan kemitraan yang kuat. Pengguna platform ini sering memberikan ulasan, melihat ulasan pengguna bisa saja dilakukan secara manual tetapi hal ini akan memberikan dampak yang kurang efektif, sehingga perlu dilakukan secara otomatis dengan analisis sentiment. Penelitian ini bertujuan untuk menerapkan metode klasifikasi Naïve Bayes dalam analisis sentimen ulasan PegiPegi.com, dengan fokus pada pemahaman kepuasan pelanggan dan peningkatan layanan. Dengan menggabungkan pendekatan ini, penelitian ini berkontribusi pada pemahaman yang lebih dalam tentang tanggapan pengguna terhadap layanan OTA dan menyajikan hasil evaluasi model klasifikasi Multinomial Naive Bayes dengan tingkat akurasi 89,5%. Presisi tinggi di kelas Negatif menunjukkan kemampuan model untuk mengidentifikasi ulasan negatif. Namun, ada tantangan dalam mengklasifikasikan kelas Netral, menunjukkan potensi untuk perbaikan lebih lanjut. Namun demikian, skor F1 0,522 mencerminkan keseimbangan yang baik antara presisi keseluruhan dan daya ingat sehingga dapat disimpulkan algoritma naïve bayes berhasil untuk melakukan analisis sentimen.
Keywords: Analisis sentimen; naïve bayes; pegipegi.com; playstore
Abstract:Abstract: The city of Surakarta is one of the cities that is busy with local and foreign tourists because there are various kinds of interesting cultural tourism. The large number of hotels with many services and facilities…
ies makes tourists confused in choosing a hotel, so prospective hotel guests need a long time to choose the best hotel according to their desired criteria. The aim of this research is to create a tool for prospective hotel guests in making decisions on hotel selection recommendations using the TOPSIS and SAW methods. This research uses 8 hotel data points in Laweyan District, Surakarta, and hotel data obtained from the Tourism Office. The results of the McCall Test with 5 indicators, namely accuracy, reliability, efficiency, integrity, and usability, average 86%, so this system is categorized as very good.
Keywords: hotel selection; TOPSIS; SAW; decision supporter system
Abstrak: Kota Surakarta menjadi salah satu kota yang ramai dikunjungi wisatawan lokal maupun mancanegara karena terdapat berbagai macam wisata budaya yang menarik. Banyaknya hotel dengan pelayanan dan fasilitas yang banyak membuat wisatawan kebingungan dalam memilih hotel, sehingga calon tamu hotel memerlukan waktu yang lama untuk memilih hotel terbaik sesuai kriteria yang diinginkan. Tujuan dari penelitian ini adalah membuat suatu alat bantu bagi calon tamu hotel dalam pengambilan keputusan rekomendasi pemilihan hotel menggunakan metode TOPSIS dan SAW. Penelitian ini menggunakan 10 titik data hotel yang ada di Kecamatan Laweyan Surakarta dan data hotel yang diperoleh dari Dinas Pariwisata. Hasil Uji McCall dengan 5 indikator yaitu akurasi, reliabilitas, efisiensi, integritas, dan kegunaan rata-rata 86%, maka sistem ini dikategorikan sangat baik.
Kata kunci: pemilihan hotel; TOPSIS; SAW; sistem penunjang keputusan
Abstract:Abstract: The service dramatically affects the number of guests staying at the hotel. Bali is the most visited tourist area by foreign tourists. Therefore, improved service is crucial for determining the rating level of…
a hotel. This research aims to combine two data mining algorithms: clustering and classification. This research is expected to contribute to hospitality in improving the best services for tourists, especially in the City of Bali. Clustering algorithms are used to group the best number of hotels based on the four clusters selected from the k-means clustering algorithm. The classification algorithm using C4.5 determines the factors most dominant in determining the hotel rating level based on the gain ratio. The data used in this study results from observations on the website agoda.com in Bali of 51 data. The results of this study explained that cluster_0 is the highest-rated cluster, with a total number of 19 hotels found in claster_0. Data cluster0 is used for classification analysis using a decision tree, and the most dominant factor is the service factor, with an accuracy of 80%.
Keywords: data mining; kmeans; decision tree; hotel; bali;
Abstrak: Pelayanan sangat mempengaruhi jumlah pengunjung yang menginap dihotel. Bali merupakan daerah wisata paling banyak dikunjungi oleh wisatawan mancanegara. Oleh karena itu, peningkatan pelayanan sangat penting untuk penentuan level rating dari hotel. Tujuan dari penelitian ini untuk menggabungkan dua algoritma data mining yaitu clustering dan klasifikasi. Dengan penelitian ini diharapkan dapat memberikan kontribusi bagi perhotelan dalam meningkatkan pelayanan yang terbaik bagi wisatawan khususnya di Kota Bali. Algoritma Clustering digunakan untuk mengelompokkan dari jumlah hotel yang terbaik berdasarkan empat cluster yang dipilih dari algoritma clustering berupa k-means. Algoritma klasifikasi menggunakan C4.5 digunakan untuk mengetahui faktor apa yang paling dominan dalam menentukan level rating hotel berdasarkan gain ratio. Data yang digunakan dalam penelitian ini hasil observasi di website agoda.com di bali sebanyak 51 data. Hasil dari penelitian ini menjelaskan dataset cluster_0 merupakan cluster rating tertinggi dengan jumlah 19 hotel yang terdapat di cluster_0. Data cluster_0 digunakan untuk analisis klasifikasi menggunakan decesion tree, didapat faktor yang paling dominan adalah faktor layanan dengan nilai akurasi sebesar 80%.
Kata kunci: data mining; kmeans; decision tree; hotel; bali;
Abstract:This study aims to examine the relationship between employee training and development programs and customer satisfaction levels within the hospitality sector, with a particular focus on MaxOne Hotels in Makassar. Employing…
ng a mixed-methods approach, the research integrates employee surveys, customer feedback, and performance metric analysis to assess the influence of training programs on service quality and customer experiences. The findings reveal that employee training and development variables account for only 1.4% of the variance in customer satisfaction, with the remaining 98.6% influenced by other factors. Nevertheless, well-structured training program designs were shown to significantly enhance employees' critical thinking, communication, emotional regulation, and problem-solving skills. Furthermore, technology-based training demonstrates substantial potential for improving service efficiency and facilitating adaptation to operational innovations. In conclusion, while the direct impact of training on customer satisfaction is relatively minor, thoughtfully designed training programs remain essential for delivering high-quality customer experiences and sustaining competitiveness in the industry. This research offers valuable insights into strategies for optimizing training effectiveness in the hospitality sector.
Abstract:This study examines the effectiveness of training programs for room attendants in the hospitality industry, focusing on their impact on performance, job satisfaction, and retention. Using a qualitative approach, in-depth…
interviews were conducted with 20 room attendants and 10 housekeeping managers across various hotel segments. The findings reveal that while initial training typically covers basic cleaning techniques and safety protocols, it often lacks depth in advanced methods and customer service skills. Challenges such as time constraints and reliance on informal learning are common, affecting the consistency and quality of training. Effective training programs were identified as those that provide comprehensive, ongoing instruction and incorporate innovative methods like virtual reality and gamified learning. The study also highlights the importance of mentorship programs and regular feedback to enhance training outcomes. Recommendations for improving training programs include developing detailed curricula, addressing time constraints, and adapting to emerging trends. By implementing these strategies, hotels can enhance room attendants' skills, satisfaction, and overall service quality, leading to improved guest experiences and operational success.
Abstract:This study examines the implementation of the Local Tax on Certain Goods and Services (PBJT) in hotels in Bogor Regency and its impact on Regional Original Revenue (PAD) after Law No. 1 of 2022. Using a quantitative approach…
oach based on Edward III’s model, the study analyzes communication, resources, disposition, and bureaucratic structure. Data from 684 respondents were analyzed using multiple linear regression. Results show PBJT significantly increases PAD (R²: 71.7%–76.0%; p < 0.001), with bureaucratic structure and resources as the most influential factors. However, challenges remain, including unclear communication, limited resources, and low taxpayer compliance. Strengthening institutional capacity, improving coordination, and enhancing taxpayer compliance are recommended to optimize PAD.