PERAMALAN PENJUALAN PRODUK PAKAIAN DENGAN KOMBINASI METODE FUZZY TIME SERIES DAN ALGORITMA PARTICLE SWARM OPTIMIZATION
Total View This Week0

Institusion

Universitas Sriwijaya

Author

THEO VHALDINO (STUDENT ID : 09021381419087)
Rifkie Primartha (LECTURER ID : 0001067709)
Kanda Januar Miraswan (LECTURER ID : 0009019002)

Subject

R858-859.7 Computer applications to medicine. Medical informatics 

Datestamp

2019-09-30 04:15:05 

Abstract :
One of the sales forecasting is to prevent over production and under production which causes the company to lose the opportunity to sell its production and can help the company to conduct sales strategies in the future. In this study, forecasting is done using the Fuzzy Time Series method because it can project future data based on data in a timely manner. To improve forecasting accuracy, optimization using the Particle Swarm Optimization (PSO) algorithm is used to change the interval pattern of linguistic values in the Fuzzy Sets process. The advantages of the PSO algorithm have high decentralization with a simple implementation so that it can solve optimization problems efficiently. Error rates are calculated using MSE and AFER. Based on testing predicting clothing products with Fuzzy Time Series using PSO Optimization obtained a decrease in the results of the average error rate (error) of MSE = 7451450.145 and AFER = 0.234% for Kaos data types, MSE = 2115209.254 and AFER = 0.090% for Shirt data types MSE = 1398279.2 and AFER = 0.087% for Jacket data types with 24 test data. K 

File :
RAMA_55201_09021381419087_0001067709_0009019002_01_front_ref.pdf
RAMA_55201_09021381419087_0001067709_0009019002_02.pdf
RAMA_55201_09021381419087_0001067709_0009019002_03.pdf
RAMA_55201_09021381419087_0001067709_0009019002_04.pdf
RAMA_55201_09021381419087_0001067709_0009019002_05.pdf
RAMA_55201_09021381419087_0001067709_0009019002_06.pdf
RAMA_55201_09021381419087_0001067709_0009019002_07_ref.pdf
RAMA_55201_09021381419087_0001067709_0009019002_08_lamp.pdf