Abstract:
In response to the Covid-19 pandemic era, the "school from home" and
"work from home" measures that been implemented have significantly changed
activity patterns. Activity patterns that are normally diverse and unbound become
monotonous and constrained. The phenomena of "work from café" has evolved in
the middle of monotony, boredom, and tension as a result of changing legislation
and activity patterns, as well as the continued development of the food and
beverage industry sector.
Since the pandemic, people have begun to make work from cafes as a
habit. Despite the pandemic, there is still a significant demand for trying new
cafes that cater to users' preferences. To meet this demand, this web application
has been developed to provide cafe recommendations based on user preferences
and search location. The website is designed to be user-friendly and efficient, so it
making easy for users to discover new cafes that meet their criteria. With its
sophisticated location-based recommendation algorithm and user-friendly
interface, this website is a valuable tool for anyone looking to discover new and
trending cafes that cater to their personal preferences.
Whereas the goal from the developer is to build a website that provides
cafe recommendations to users based on their location input and personal
preferences. The website will utilize a location-based recommendation approach,
which takes into account the proximity of the cafes to the user's set location, as
well as the preferences of similar users. The first step will be to gather data about
cafes, their locations, and, as well as user preferences. The data will then be
preprocessed, and a suitable recommendation algorithm, such as Collaborative
Filtering, will be chosen and implemented.
