Analisis Eksplorasi Dan Visualisasi Profil Superhost Airbnb Kota Madrid Dan Amsterdam

Abstract

Superhost Airbnb is an experienced host and provides excellent service to its customers. Superhost has features that can increase the number of bookings and revenue. SuperHost profile is one thing that can be used as a reference for other hosts to improve the quality of service. In this study, an analysis of exploration and visualization of Airbnb hosts' data in the city of Amsterdam and the city of Madrid to find out the profile of superhost from the aspect of price and consumer reviews. The city of Amsterdam and the city of Madrid are chosen because the two cities are the leading destinations for tourists in Europe. The study was conducted using a machine learning approach that has four work steps, namely understanding business processes, data retrieval, data processing, and exploratory analysis and data visualization. The tools used in this study are Jupyter Notebook with the Python programming language. The results obtained from this study are superhost in Madrid, mostly offering rental prices in the price range of $60 - $80. They get the highest reviews from customers based on cleanliness, communication, and check-in. As for Amsterdam, the superhost offers the most rental prices in the price range above $ 140. Superhosts in this price range gets the most reviews from customers in all review groups.

Exploratory data analysis of crime report

“…Over the last few decades, academics have introduced various tools and techniques to visualize hidden correlations among data variables using simplistic diagrams and charts [2]- [8]. Visual data analysis aid domain-specific data interpretation such as analysis of CRISPR/Cas9 screens [2], analysis of container shipping slot bookings [9], analysis of executive functions during childhood [10], analysis of kindergarten students log data [11], sodium and potassium coronate stability [12], fault injection campaigns [13], employee demographics and earnings [14], airport waiting times [15], analysis of medical data [16] to perform analytics tasks, and analysis of Airbnb's super host profile [17]. Crime is a risk that must be faced and managed.…”

Visualization of Amsterdam Airbnb Business Performance using Customer Reviews

“…Current studies have examined as follows. Airbnb's service quality attributes effects on customer satisfaction (Ju et al, 2019), price determinants (Wang & Nicolau, 2017), the construction of home feeling (Zhu et al, 2019), trust evolution (Ert & Fleischer, 2019), super host profile (Setiawan, 2020b), impacts of host quality and quantity attributes (Xie & Mao, 2017), development in Paris (Heo et al, 2019), user review comments (Cheng & Jin, 2019), geospatial analysis (Setiawan, 2020a), and dynamic pricing strategies (Gibbs et al, 2018;Oskam & Boswijk, 2016), price factors (Moreno-Izquierdo et al, 2020), and behaviour (Oskam et al, 2018).…”