RANCANG BANGUN SISTEM PERAMALAN PERMINTAAN JUMLAH KEBUTUHAN PASOKAN LISTRIK INDUSTRI PERUSAHAAN MENGGUNAKAN METODE SINGLE EXPONENTIAL SMOOTHING : StudiKasus PT. Krakatau Daya Listrik

摘要

Energilistrikmerupakansumberenergipentingbagikehidupanmanusiamisalnyasajapadalingkunganindustri PT. Krakatau DayaListrik.Peningkatanpemakaiankebutuhanlistrikmengharuskanpihakpenyediadanpengelolakebutuhanenergilistrikmampumengelolapendistribusianlistrikkepadakonsumentersebutdenganbaik.Seiringberjalannyawaktuperluadanyaperhitunganuntukmengetahuipemakaiandayalistrik di masamendatang.Salah satumetode yang digunakanuntukmelakukanprediksitersebutadalahmenggunakanmetode Single Exponential Smoothing.Setelahdilakukanpengujiandihasilkanbahwahasildariperamalan (forecasting) penggunaandayalistrikdarikonsumen PT. Krakatau DayaListrikdenganmenggunakan data daritahun 2006 sampai 2013 dapatdiketahuibahwahasilperamalanpadatahun 2014 adalahmasing-masingkonsumen KS (1472585 MWH) denganpersentasekesalahanterkecil MAPE 8,69%, konsumen KSG (84292 MWH) denganpersentasekesalahanterkecil MAPE 12,72%, konsumenumum (133293 MWH) denganpersentasekesalahanterkecilMAPE 26,61%. Denganpersentasedibawah 30% dapatdiartikanperamalantersebutakuratdanbaikuntukmetodeSingle Exponential Smoothing yang diterapkandalampenelitianini.udElectrical energy is an important source of energy for human life for example in industrial environments PT. Krakatau DayaListrik. Increased consumption of electricity needs require the provider and manager of the electrical energy needs are able to manage the distribution of electricity to consumers well. Over time the need for calculations to determine the power consumption in the future. One method that is used to make these predictions is using Single Exponential Smoothing. After testing is produced that results from the prediction (forecasting) of electric power from consumers PT. Krakatau DayaListrik using data from 2006 to 2013 can be seen that the forecasting results in 2014 were each consumer KS (1,472,585 MWH) with the smallest percentage error MAPE 8.69%, consumer KSG (84,292 MWH) with the smallest percentage error MAPE 12.72%, general consumer (MWH 133,293) with a percentage of 26.61% MAPE smallest error. With a percentage below 30% can be interpreted accurately forecasting and good for Single Exponential Smoothing method applied in this study.