No abstract

Covid-19 has been declared a global pandemic by WHO. This affects all aspects of human life, including education. The entire teaching and learning process during the Covid-19 pandemic was carried out online or by implementing e-learning. The online system of study intends to avoid human contact. This study aims to look at the media used to implement e-learning, considerations in choosing e-learning media, as well as the advantages and disadvantages found in implementing e-learning. There are six English lecturers who teach Tourism English at Tourism Department of Bali State Polytechnic. The data used in this study were obtained from questionnaires distributed online. The data is then analyzed by looking for a percentage and describing it.

Keberhasilan desa wisata untuk mendatangkan wisatawan tergantung kepada jaringan distributor pariwisata seperti perusahaan transport, tour operator, dan travel agent yang dikenal sebagai rantai pasokan pariwisata (Tourism Supply Chain-TSC). Tujuan pengabdian kepada masyarakat ini adalah mewujudkan TSC di Desa Wisata Pelaga agar dapat mendatangkan wisatawan secara berkesinambungan melalui TSC. Pengabdian tahun 2020 adalah untuk mempersiapkan persyaratan utama desa wisata yaitu atraksi, amenities, dan akomodasi. Penelitian dilakukan dengan metode deskriptif kualitatif dengan cara wawancara, observasi dan dokumentasi. Data kemudian dianalisis dengan metode pattern matching. Hasil penelitian menyatakan bahwa khusus pada Desa Wisata Pelaga atraksi wisata (keindahan alam dan agrowisata) telah siap sebagai produk wisata, akan tetapi tidak ada akomodasi dan amenities. Terkait hal tersebut maka dua buah kamar di dua keluarga dijadikan percontohan homestay, pelatihan Bahasa Inggris dan kuliner diberikan kepada pemuda desa, serta pembuatan brosur, website dan papan penunjuk arah.

ABSTRACT Purpose: This study aims to analyze the application of marketing mix in this case 7Ps (product, price, place, promotion, people, process, and physical evidence) in increasing the number of meetings at a 5-star hotel located in Kuta area, Bali, Indonesia. Research methods: Data collection was carried out by observation, interviews, documentation, and questionnaires with a total of 150 respondents from professional conference organizers who had held a meeting at the hotel. The analysis technique used in this study is qualitative and quantitative analysis.  Results and discussion: The implementation of the marketing mix applied by the hotel is such as providing a meeting place including facilities and meeting equipment, providing prices following client budgets, promoting using brochures, websites, through sales calls and telemarketing, routinely checking the conditions of the meeting place. The most effective variable influencing the increase in the number of meeting events is by looking at the results of the beta standard coefficient of the largest value, namely the physical evidence variable with the largest value of 0.266 with sig 0.00 which means that the physical evidence variable most effectively influences the number of meetings Implication: The factors causing the ineffectiveness of the variable of the marketing mix based on the results of the interview are less than optimal employee performance and promotions that are carried out less and are less effective in selling meeting packages. Keywords: marketing mix, meeting events, multiple linear analysis regression.

Abstract:The aim of this study is to determine the cluster of homogenous financial centers by using hierarchical clustering analysis, and to define in which same cluster Istanbul city takes part with other financial centers. Thirty eight countries financial center and sixteen variables were included in the analysis. For analyzing data, Ward's method of hierarchical clustering analysis technique was applied and a Squared Euclidian distance measure was used. According to the analysis results, countries were grouped in four different clusters. Sydney, Vienna, Brussels, Toronto, Helsinki, Paris, Frankfurt, Tokyo, Amsterdam, Madrid, Stockholm, Zurich, London and New York were gathered in Cluster 1. Rio De Janerio, Prague, Shanghai, Johannesburg, Milan, Kuala Lumpur, Warsaw, Lisbon, Moscow, Bangkok, Athens, Tel Aviv, Seoul and Almaty were gathered in Cluster 2, and Istanbul found its place in Cluster 3 sharing with Mexico city, New Delhi, Jakarta, Cairo and Bogota. Dublin, Doha, Singapore and Dubai were gathered in Cluster 4. The emprical results clearly showed that Istanbul city has not homogenized with the international/global financial centers yet.