@thesis{thesis,
		author={Effendy  Muhammad Azis},
		title ={PENGELOMPOKAN DATA PELAMAR KERJA DI BURSA KERJA KHUSUS SEKOLAH MENENGAH KEJURUAN NEGERI 1 SUKABUMI MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING},
		year={2019},
		url={https://eprints.ummi.ac.id/1170/},
		abstract={BKK is held in schools to help junior high school graduates in finding work, including at SMK Negeri 1 Sukabumi. Every year BKK establishes relationships with agencies that require high school graduates. However, each company has its own standards for prospective employees. For example: must be the latest graduates, high achieving students, rapot grades, and general. K-Means algorithm can help classify job applicants that fit the criteria of the company, can select prospective workers to be registered for employment tests in the company. The purpose of this research is clustering job applicants so that they can help BKK in grouping job applicants with criteria that are in line with the company with 3 criteria. The data used as many as 25 as until to draw some conclusions, because it has represented various types of job applicants. The data is calculated using the K-Means Algorithm and testing using web grouping job applicants. From the results of the test, 4 people entered a special company, 16 people entered national & international companies, 5 people entered the corporate & Jabodetabek companies.}
		}