Sistem Rekomendasi Pembelian Laptop dengan K-Nearest Neighbor (KNN) - Sheeren Hendrik Anggela; Leo Willyanto Santoso; Justinus Andjarwirawan (Universitas Kristen Petra, 2022)
Over a decade, the number of people who needs a laptop for their job is increased because of its slim design and internal battery that makes it easier to carry anywhere, if compare to an old-fashioned computer. However, the choices of laptop specifications are various, namely the laptop model, brand of the processor, the speed of processor, size of the screen, RAM, price, etc. Not all people knows the indicator of choosing the laptop that fit to their wants and needs. In this study, the process of recommendation system is used a methods namely K-Nearest Neighbor Collaborative Filtering. This method will estimate the distance with Euclidean formula between the users' criteria and the survey. The closest distance is considered as the recommendation. The data testing is done through counting the accuration based on the recommendation's result which is given to the user. The survey is used for counting the total of valid recommendation. he results of this study using a satisfaction survey that has been surveyed to 10 laptop shop employees. Based on the survey results, average accuracy of testing the recommendation results is 84%. Testing the appearance of the website is also quite good because most users give a value or rating of 4 or 5. Based on the testing results, it can be concluded that the appearance of the website and the results of recommendations with the K-Nearest Neighbor method is pretty good because they are in accordance with the criteria and needs of users.