KLASIFIKASI PENGELOMPOKAN DALAM MELIHAT KESESUAIAN DAYA PELANGGAN KOTA LHOKSEUMAWE - Andik Bintoro; Safwandi Safwandi (STMIK Budi Darma, 2018)
Classification of K Nearest Neighbors in this study to determine the grouping in seeing the suitability of the installed household electricity customers. Then the system built can see customers who want to know the amount of power given and want to add new. Conversely, if customers who want to reduce the power that has been given because it is too large with the condition of houses that are not large and not much use, can be seen in this system. The purpose of this study is to facilitate old customer customers in seeing the installed power with a variable amount of air conditioner (AC), number of refrigerators, number of washing machines and other electronic quantities based on the grouping of test data. first adjusted to the new test data. The process of the K-Nearest Neighbor method is to input the customer's name with the value of the amount of air conditioner (AC) with a value of 2, the number of refrigerators with a value of 2, the number of washing machines with a value of 1 and the number of other electronics with a value of 7. Then the data is seen with distance closest is 1.73205 by being trained by seeing neighbors nearby in training training. Furthermore, training of the data was obtained by customers with ID P-05 found in class C2 classifications. The results of this system are in the form of customer grouping which is categorized into 4 ampere, 6 ampere or 12 ampere category classification types, each of which is seen from the amount of power installed. This research is expected to help PLN customers of the city of Lhokseumawe in knowing the old customers who are included in the type of grouping.Keywords: Classification, Electrical Power, K-Nearest Neighbors