Writer / NIM
SULASTRI R. PAKAYA / 413413005
Study Program
S1 - STATISTIKA
Advisor 1 / NIDN
H.S. PANIGORO / 0001058501
Advisor 2 / NIDN
RESMAWAN, S.Pd., M.Si / 0013048801
Abstract
Sulastri R. Pakaya, 2018. Peramalan Penjualan Listrik dengan Membandingkan
Metode Double Eksponential Smoothing Brown dan Double Eksponential
Smoothing Holt (Studi Kasus Pada PLN Cabang Gorontalo). Skripsi. Gorontalo.
Program Studi Statistika. Jurusan Matematika. Fakultas Matematika dan Ilmu
Pengetahuan Alam. Universitas Negeri Gorontalo.
Pembimbing : (1) Hasan S. Panigoro,S.Pd.,M.Si, (2) Resmawan,S.Pd.,M.Si
Peramalan merupakan suatu kegiatan untuk memprediksi kejadian di masa akan
datang dengan menggunakan data dan informasi di masa lalu. Peramalan dapat
membantu perencanaan yang efektif danh efisien. Dalam penelitian ini, dilakukan
perbandingan antara metode peramalan Double Eksponential Smoothing Brown
dan Double Eksponential Smoothing Holt. Perbandingan kedua metode tersebut
dilakukan dengan menggunakan data penjualan listrik PLN Cabang Gorontalo.
Data hipotesis yang disajikan menunjukan adanya pola data Trend, sehingga
peramalan dapat dilakukan dengan metode Double Eksponential Smoothing. Dalam
hal ini semakin kecil nilai mean square error(MSE), Mean Absolute Error (MAE),
Standard Deviation of Error (SDE), Sum of Squared Error (SSE), dan Mean
Absolute Percentage Error (MAPE) yang diperoleh maka hasil ramalan tersebut
semakin baik. Hasil yang diperoleh menunjukan metode Double Eksponential
Smoothing Holt dengan =0,4 dan =0,1 mengasilkan nilai MSE = 879145,15;
MAE = 815,25; SDE = 979,32; SSE = 10549741,80; dan MAPE = 2,21; sementara
Double Eksponential Smoothing Brown menghasilkan nilai MSE = 914796,58;
MAE = 840,55; SDE = 998,98; SSE = 10977558,98; dan MAPE = 2,28. Hal ini
menjukan bahwa Double Eksponential Smoothing Holt yang menghasilkan forecast
error terkecil dibandingkan Double Eksponential Smoothing Brown. Namun selisih
persentase penyimpangan hasil peramalan dari kedua metode tersebut hanya sekisar
0,07%.
Kata Kunci: Penjualan Listrik Gorontalo, DES Brown, DES Holt
Pakaya, Sulastri R. 2018.. Forecasting of Electricity Sale by Comparing Browns
and Holts Double Exponential Smoothing Methods (Case Study in State Electricity
Company (PLN) Branch of Gorontalo). (Case Study in State Electricity Company
(PLN) Branch of Gorontalo). Undergraduate Thesis. Gorontalo. Undergraduate
Program of Statistics. Department of Mathematics. Faculty of Mathematics and
Natural Sciences. State University of Gorontalo.
Principal Supervisor: (1)Hasan S. Panigoro,S.Pd.,M.Si, Co-supervisor:
(2)Resmawan,S.Pd.,M.Si
Forecasting is an activity to predict future occurrences by utilizing past data and
information. It is employed to conduct effective and efficient planning. The research
aims to compare between forecasting methods of Double Exponential Smoothing
by Brown and by Holt in data of electricity sale of State Electricity Company
(PLN) branch of Gorontalo. The study employed Double Exponential Smoothing
forecasting method based on presented hypothesis data, in which it shows trend data
pattern. The smaller the amount of Mean Square Error (MSE), Mean Absolute Error
(MAE), Standard Deviation of Error (SDE), Sum of Squared Error (SSE), and Mean
Absolute Percentage Error (MAPE) values, the more accurate the forecast result it
produces. The result shows that Double Exponential Smoothing by Holt results as
follows: MSE = 879145.15; MAE = 815.25; SDE = 979.32; SSE = 10549741.80;
and MAPE = 2,21; on the other hand, Browns method results in MSE = 914796.58;
MAE = 840.55; SDE = 998.98; SSE = 10977558.98; and MAPE = 2.28. The result
signifies that Holts method produces lesser forecast error than that of Brown, by
error percentage gap of 0.07% (= 0.4; = 0.1).
Keywords: Electricity sale in Gorontalo, DES Brown, DES Holt.
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