@thesis{thesis,
		author={Haris  Abdul and Kuswardani  Dwina and Lestari  Prilia Wanda},
		title ={Penerapan Metode K-Nearest Neighbor (KNN) Untuk Klasifikasi Data Pengaduan Masyarakat DPR RI Sesuai Dengan Bidangnya},
		year={2019},
		url={http://156.67.221.169/4365/},
		abstract={The House of Representatives of the Republic of Indonesia (DPR RI) is a high state institution representing the people in the Field of Government. One of the DPR's duties is to listen to the aspirations or complaints from the public. The field of public complaints is the Legal, Economic and Labor Sector. The difficulty of classifying community complaints data with their fields is thus made this research to classify community complaint data according to their fields. This research was conducted using the K-Nearest Neighbor algorithm with a text similarity approach using cosine similarity. The result of this research is an application that can automate the classification of public complaints based on the field of complaints so that it will be easier for administrators to manage these complaints}
		}