Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Jurnal Poros Teknik Mesin Unsrat
Febry Aprily Hontong
Unknown Affiliation
Automotive Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
PREDIKSI KEBUTUHAN ENERGI LISTRIK SULAWESI UTARA MENGGUNAKAN ARTIFICIAL NEURAL NETWORK DAN METODE EXPONENTIAL SMOOTHING Febry Aprily Hontong; Tritiya Arungpadang; Johan S C Neyland
JURNAL POROS TEKNIK MESIN UNSRAT Vol. 5 No. 2 (2016): Jurnal Poros Teknik Mesin Unsrat
Publisher : Fakultas Teknik Jurusan Teknik Mesin Universitas Sam Ratulangi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

To predict the electrical energy need of North Sulawesi for one year ahead requires correct methods. The reliable methods used for the prediction task in this research are Artificial Neural Network and Exponential Smoothing. The prediction results using Artificial Neural Network are 110.38, 112.62, 111.56, 108.05, 107.95, 110.32, 109.90, 110.58, 113.26, 107.11, 115.60, 105.40 GWh. The prediction results using Exponential Smoothing are 112.32, 112.70, 113.07, 113.45, 113.82, 114.19, 114.57, 114.94, 115.32, 115.69, 116.07, 116.44 GWh.   Key words: Artificial Neural Network, Exponential Smoothing, Prediction, Electrical Energy Need.
Co-Authors Johan S C Neyland Tritiya Arungpadang