Implementasi Algoritma K-Nearest Neighbor Berbasis Website pada Sistem Rekomendasi Persewaan Alat Camping

Development of information technology currently provides opportunities for business owners to improve efficiency and quality of service including in the camping equipment rental industry. Aygadventure as one of the camping equipment rental companies faces several operational constraints such as inefficient manual recording, long queues, and errors in data management. This study aims to design and implement a website-based rental recommendation system using the K-Nearest Neighbor (K-NN) algorithm to overcome these problems. The K-NN algorithm is used to provide product recommendations based on rental data to increase efficiency in the transaction process. The system development method uses the Prototyping method which allows system adjustments according to user needs. System testing uses several methods including white box testing, black box testing, and user satisfaction testing with satisfactory results. White box testing shows 100% successful coding results in the system, while black box testing results in full success on all features and functionalities of the system being tested. The results of the user acceptance test show an average satisfaction of 83.30%, respondents expressed satisfaction with the aspects of usability, access speed, and ease of navigation. Thus, this system successfully improves Aygadventure's operational efficiency, provides a better user experience, and increases overall customer satisfaction.