Penerapan Model K-Nearest Neighbors Dalam Klasifikasi Kebutuhan Daya Listrik Untuk masing-masing Daerah di Kota Lhokseumawe

Sadli, M and Fajriana, Fajriana and Fuadi, W and Ermatita, Ermatita and Pahendra, I (2018) Penerapan Model K-Nearest Neighbors Dalam Klasifikasi Kebutuhan Daya Listrik Untuk masing-masing Daerah di Kota Lhokseumawe. Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering), 5 (2). pp. 11-18. ISSN p-ISSN 2355-5068e-ISSN2622-4852

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Abstract

Classification for electric power requirements for each region is very necessary in order to describe the power conditions needed This is very important for new customers to want to know the power provided, otherwise old customers can also see and reduce power or add power according to needs. The variable used is the area of ​​the house, the amount of electric power that will be used and has been used, the combined income of parents (dirty) / month, the amount of power of the lights at home, then continued with the classification of the estimated electrical power provided. Furthermore, the classification used is the determination of the class of Tariff / Power R-1/450 VA subsidies, R-1/900 VA subsidies, R-1/900 VA-RTM (capable Household) non-subsidized, R-1/1300 VA non-subsidized, and Tariff / Power class R-1/2200 VA non-subsidized. Furthermore, for testing using training data samples as many as 20 sample data from each customer that will be seen with the closest neighbors. For power samples consist of testing variables and classification types. K-Nearest Neighbors (KNN) test for house area is 3, power 3, income 2, total power, 3 and energy consumption used is 4. Results from this research is the application of technology in the KNN in the determination of the power requirements for each region at Lhokseumawe City.

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