PREDIKSI PENEMPATAN ODP (OPTICALDISTRIBUTION POINT) BEDASARKAN TITIK BANGUNAN YANG DIKLASTERISASI DENGAN METODE K-MEANS BERBASIS ANDROID
Total View This Week0
Total View This Week0
Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
PRABOWO, JOBLI ANGGA HANI
Yosrita, Efy
Suliyanti, Widya NIta
Yosrita, Efy
Suliyanti, Widya NIta
Subject
Teknik Informatika
Datestamp
2022-09-21 01:44:31
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.
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.
Download
book
BibTex
Latex, Jabref
cloud_download
Original Resource
url resource Institution
