@thesis{thesis,
		author={Asura  Mayang and Aziza  Rosida Nur and Praptini  Puji Catur Siswi},
		title ={Aplikasi Controlling dan Monitoring Smart Home dengan Fitur Notifikasi Penggunaan Listrik Rumah Tangga Menggunakan K-means Clustering},
		year={2020},
		url={http://156.67.221.169/4193/},
		abstract={The use of energy in the household sector that is less efficient has an impact on the sales of electrical energy for household customer groups which account for 42.25% of the total percentage of Indonesian electricity consumption according to the 2019 PLN statistical data. The contributing factors are behavioral factors that influence electricity consumption patterns, Lack of understanding or good awareness and lack of motivation which has an impact on the internal attitude of individuals who are still ignorant of energy-saving behavior. So that we need an incentive to behave energy efficient. This study aims to encourage energy-saving behavior by providing real-time information about electricity consumption and analyzing the electricity consumption patterns of smart home application users. The data processed is the control activity data from the sensor readings using the Kmeans Clustering Algorithm. The results of the cluster analysis obtained cetroid data for the normal consumption level cluster, namely 0.00370, and data centroid for the high consumption level cluster, namely 0.01679. Clusters with high consumption levels will be notified via the smart home application on an android smartphone. From the results of clustering, a cluster evaluation was carried out using the Davies Bouldin Index, the DBI figure was 0.467798034 which was close to 0, so it can be said that the cluster is optimal.}
		}