@thesis{thesis,
		author={Karangan  Firesta},
		title ={Klasifikasi Penerima Beasiswa Kartu Indonesia Pintar (KIP-Kuliah) Menggunakan Metode K-Nearest Neighbor Studi kasus: Institut Teknologi Kalimantan},
		year={2023},
		url={http://repository.itk.ac.id/19939/},
		abstract={The Indonesia Smart Card (KIP-Kuliah) Scholarship program is one of the goverment's efforts to help students who have economic limitations. The K-Nearest Neighbor (KNN) method is used to classify prospective scolarship recipients baesd on relevant variabels. The research variabels used were the father's uccupation, mother's uccupation, parent's combined income, number of dependents, and avarage report card scores. Applying the KNN method will obtain the results of the classification of KIP-Collage scholarship recipients. The data used in this study is divided into training data and testing data.Training data using data from study is divided into training data and testing data. Training data using data from KIP-Collage shcolarship applicants at the ITK in 2020-2021 and this testing using data from KIP-Collage shcolarship applicants at ITK in 2022 in this research, a teqchnique called random oversampling was needed to increase the number of samples i the minority class and produce better accuracy  values. The proportion of dataset division in this study uses 70:30, 75:25, and 80:20 with the method of random oversampling to obtain the best model on the testing data with an accuracy of 91% in the proportion of 70:30 using the best k, namely k=1}
		}