@thesis{thesis,
		author={PRABOWO  JOBLI ANGGA HANI and Suliyanti  Widya NIta and Yosrita  Efy},
		title ={PREDIKSI PENEMPATAN ODP (OPTICALDISTRIBUTION POINT) BEDASARKAN TITIK BANGUNAN YANG DIKLASTERISASI DENGAN METODE K-MEANS BERBASIS ANDROID},
		year={2019},
		url={http://156.67.221.169/4457/},
		abstract={Population growth is increasing with the growth of the number of buildings as a
place of residence or as a business for example in the area Cipondoh Makmur, Kec.
Cipondoh, Kota Tanggerang, Banten. Therefore, the application of prediction of ODP
placement using the algorithm method K-means to facilitate employees PT. Telkom
Indonesia Regional 2. K-Mean is an algorithm that partitions data into clusters so that
different characteristics data are grouped into other groups.results of the
implementationK-means method of obtainingclustersC1There are 17 data, then 1 data
on the clusterC2and 17 DataC3. Each of the clusters have different centroid values C1
latitute-6.185.45 longitude 106,670,232, C2 latitute-617,317 longitude 106,718,842 and
c3 Latitute-6,188,225 Longitute 106,673,564. Iterating on the K-means algorithm above
stops at the 7th iteration. The application has an accuracy rate of 88%, a conformity
prediction of 100% and a 65% precision level.}
		}