Metode K-Means dalam Visualisasi Berbasis Google Map terhadap Klasterisasi Koordinat BTS (Base Transceiver Station)
DOI:
https://doi.org/10.37034/jsisfotek.v4i3.143Keywords:
Data Mining, K-Means, Clustering, Google Map, Base Transceiver Station (BTS)Abstract
The supervision of the Telecommunication Tower or Base Transceiver Station (BTS) in Kerinci Regency is carried out by the Kerinci Regency Communication and Information Office. Supervision is carried out by monitoring and monitoring all BTS locations in Kerinci Regency. The problem faced by the Supervisory Team is the grouping of BTS based on the proximity of the distance between BTS based on the number of supervisory teams. This study aims to make it easier for the BTS Supervisory Team to carry out supervision by clustering coordinate points based on the proximity of the distance between BTS based on the number of supervisory teams with visualization based on google map. BTS coordinate data is used as a reference point for grouping. The data used in this study is the BTS coordinate point data in 2021, sourced from the E-Government Service Division of the Communication and Information Office of Kerinci Regency. The dataset consists of 78 BTS coordinate points. Data processing in this study uses the clustering method using the K-Means algorithm. The results in this study obtained 3 BTS Clusters, namely Cluster 1 (L2) Near Distance (JD), Cluster 2 (L1) Medium Distance (JM), Cluster 3 (L3) Long Distance (JJ). The results of visualization of the BTS cluster based on google map provide convenience for the BTS supervisory team in conducting surveillance based on the cluster
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