Efficient and Affordable Vacation Planning: A K-Nearest Neighbors Approach

Abstract

Taking an occasional recreational vacation is essential for many individuals, as it provides a much-needed break for both the body and mind from the pressures of daily life. However, the high cost of vacationing, both internationally and locally, prevents many from affording a vacation. This leads to many individuals choosing to spend their holidays with extended family or in their rural homes. To promote domestic tourism, initiatives such as 'Tembea Kenya' have been introduced to boost the tourism sector in the country. However, there are other challenges associated with traditional accommodation facilities, such as a lack of privacy, limited space, numerous restrictions, and hygiene concerns, particularly during the COVID-19 crisis. This study aims to address these challenges by developing a technological solution that allows individuals to make reservations for vacation homes, eliminating the cost of renting a house. The solution is a web-based application that utilizes the K-Nearest Neighbors machine learning algorithm to classify homes based on available features. The goal is to provide an affordable and personalized vacation experience for all.