Implementasi Data Mining Menggunakan Algoritma Fp-Growth pada Analisis Pola Pencurian Daya Listrik - Annisa Almira; Suendri Suendri; Ali Ikhwan (Teknik Informatika Universitas Pamulang, 2021)
Electricity is one of the main needs that is most widely used by the community, both for household needs and industrial needs. Due to the large number of people's needs for the use of electricity, some consumers commit fraud or theft of electric power to reduce usage costs so that they are not in accordance with the recorded power consumption. Therefore PT. PLN Persero forms a team for Controlling the Use of Electricity or P2TL which aims to examine and take action to resolve the PLN installation or the installation of electricity users from PLN. The problem that occurs in this case is that in looking at the types of electric power theft that occur to customers who commit fraud, they still use the manual method, which is to determine the type of electricity theft that mostly uses catches through the official report, thereby slowing down the P2TL party to determine the target of operation or the type of violation. potential that often occurs in the Padangsidimpuan UP3 area. The purpose of this study is to build a website-based information system using the fp-growth algorithm data mining which aims to make it easier for P2TL parties to see how patterns of electricity theft that often appear, making it easier for officers to determine operating targets more quickly. This research uses the fp-growth algorithm with the stage of generating the conditional patten base, the stage of generating the conditional pattern tree and the stage of searching for frequent items. The results obtained from this study are the percentage value of the level of certainty of each item that appears so that it can be used as a reference in determining the type of electric power theft pattern that often appears using a website-based information system.