scholarly journals Optimasi Prediksi Dengan Algoritma Backpropagation Dan Conjugate Gradient Beale-Powell Restarts

2018 ◽  
Vol 3 (3) ◽  
pp. 370-380
Author(s):  
Anjar Wanto
Keyword(s):  
Conjugate Gradient ◽  
Price Index ◽  
Consumer Price Index ◽  
Optimization Process ◽  
Backpropagation Algorithm ◽  
Index Data ◽  
Health Group ◽  
Architectural Model ◽  
Architectural Models ◽  
Do So

Optimization of a prediction (forecasting) is very important to do so that the predicted results obtained to be better and quality. In this study, the authors optimize previous research that has been done by the author using backpropagation algorithm. The optimization process will use Conjugate Gradient Beale-Powell Restarts. Data to be predicted is Consumer Price Index data based on health group from Medan Central Bureau of Statistics from 2014 until 2016. Previous research using 8 architectural models, namely: 12-5-1, 12-26-1, 12-29 -1, 12-35-1, 12-40-1, 12-60-1, 12-70-1 and 12-75-1 with best architectural models 12-70-1 with an accuracy of 92%. In contrast to previous research concentrating on finding accuracy using backpropagation, this study will optimize the backpropagation with Conjugate Gradient Beale-Powell Restart, which not only focuses on accuracy but also the convergence of the two algorithms and the translation of predicted results, which is not done in a previous study. This research will use the same architectural model as the previous research and will get the result with the accuracy of 92% with the best architectural model that is 12-70-1 (same as previous research). Thus, this model is good enough for prediction even with different algorithms, since the accuracy of converging backpropagation with Conjugate Gradient Beale-Powell Restarts.

scholarly journals Desarrollo arquitectónico de tres especies de Acacia

2017 ◽  
pp. 7
Author(s):  
Amparo Echeverry-Gómez ◽  
Henricus F.M. Vester
Keyword(s):  
Related Species ◽  
Development Pattern ◽  
Vegetative Development ◽  
Development Patterns ◽  
Legume Trees ◽  
Branching Patterns ◽  
Architectural Model ◽  
Architectural Models ◽  
Do So

Studies about the vegetative development of Legume trees are relatively rare. In order to infer about the evolution of different development patterns a study of taxonomically related species is requiered. We analyzed three species of Acacia (A . collinsii, A. cedilloi and A. dolichoslachya) which according to preliminary observations show branching patterns as defined in the architectural model of Troll or Champagnat in order to answer the question which is the evolutionary relation between these models. We describe the development pattern of these species and found that a combination of architectural models is needed to do so. We found that mixed plagiotropic axes in A. collinsii are relayed by orthotropic axes during development and open a discussion to the evolutionary origen of the mixed axis.

scholarly journals Penerapan Metode Backpropagation Dalam Memprediksi Jumlah Penjualan Oli Shell

2019 ◽  
Vol 1 ◽  
pp. 396
Author(s):  
Chairul Fadlan ◽  
Irfan Sudahri Damanik ◽  
Jaya Tata Hardinata
Keyword(s):  
Accuracy Rate ◽  
Backpropagation Algorithm ◽  
Sales Data ◽  
Architectural Model ◽  
Architectural Models

The application of a prediction is very important to do in research, so that research becomes faster and directed. Just as in predicting the number of shell oil sales, studies and the use of appropriate methods are needed to obtain optimal results. The data used in this study is sales data from PT. Mitra Petra Sejahtera Kota Medan from 2012 to 2017. The algorithm used to make this prediction is the backpropagation algorithm. This algorithm is used to predict future results based on previous data. There are 6 architectural models used in the backpropagation algorithm, among others, 4-2-1 which will later produce predictions with 83% accuracy, 4-3-1 = 78%, 4-4-1 = 83%, 4- 5-1 = 78%, 4-8-1 = 100% and 4-10-1 = 72%. The best architecture of these 6 models is 4-8-1 with an accuracy rate of 94% with a level of Error 0.001, MSE = 0.04133616. so this architectural model is good enough to be used to predict the amount of shell oil sales.

scholarly journals Estimasi Nilai Tukar Petani Subsektor Tanaman Pangan Menggunakan JST pada Provinsi Sumatera Utara

2019 ◽  
Vol 1 ◽  
pp. 369
Author(s):  
Sandy Putra Siregar ◽  
Dedy Hartama ◽  
Anjar Wanto
Keyword(s):  
Exchange Rate ◽  
Household Production ◽  
Food Crop ◽  
Backpropagation Algorithm ◽  
Production And Consumption ◽  
Architectural Model ◽  
Architectural Models ◽  
The Government ◽  
Welfare Index ◽  
Central Sumatra

One way the government determines the level of welfare of farmers is to look at the development of the farmers' exchange rate index. Farmer exchange rate index (NTP) is useful in determining, measuring the ability to exchange products sold by farmers with products needed by farmers in household production and consumption. This study produced an estimate of 4 (four) years ahead from the farmer subsector index of the exchange rate index while the data was obtained from Official News published monthly by the Central Sumatra Provincial Statistics Agency (BPS). The estimation of the farmer exchange rate index will use the backpropagation algorithm, as one algorithm that is quite accurate in estimating and predicting. The problem in this study was that there was a decrease in the percentage of the farmers' exchange rate index of the food crop sub-sector in 2017 which caused a decline in the level of welfare index of farmers in the food crop subsector. This study uses 5 architectural models, that is 3-7-1, 3-15-1, 3-20-1, 3-28-1,3-40-1. Of the 5 architectures, the best is the 3-28-1 architectural model producing an epoch of 7060 with the time needed 01:19 seconds.

Dampak Penerapan Perbankan Syari’ah Terhadap Pertumbuhan Ekonomi Negara: Kajian Perbandingan Malaysia dan Indonesia

2017 ◽  
Vol 1 (1) ◽  
pp. 37
Author(s):  
Hansen Rusliani
Keyword(s):  
Gross Domestic Product ◽  
Response Function ◽  
Price Index ◽  
Vector Autoregression ◽  
Consumer Price Index ◽  
Domestic Product

Penelitian ini bertujuan untuk mengetahui dampak perbankan syari’ah terhadap pertumbuhan ekonomi di Indonesia dan Malaysia. Data yang digunakan dalam penelitian ini merupakan data primer (interview) dan data sekunder dalam bentuk bulanan yang diperoleh dari Badan Pusat Statistik Ekonomi dan Keuangan Indonesia Bank Indonesia (SEKI-BI) dan Statistik Perbankan Syari’ah Bank Indonesia (SPS-BI) serta data dari Bank Negara Malaysia dan Departemen Statistik Malaysia dalam periode waktu kurun waktu 16 tahun, 2000 sampai dengan 2015. Observasi penelitian dilakukan di Indonesia dan Malaysia untuk memperkaya analisis. Penelitian ini menggunakan Vector Autoregression (VAR), Uji Kointegrasi serta dikombinasikan dengan Response Function (IRF) dan Decomposition (FEVD) untuk melihat interaksi antara faktor makro ekonomi dengan pembiayaan dalam jangka panjang. Adapun variabel yang digunakan adalah total pembiayan syari’ah (Total Syari’ah Financing) dan Gross Domestic Product (GDP) sebagai representasi pertumbuhan ekonomi. Untuk tambahan variabel digunakan Consumer Price Index (CPI) sebagai representasi tingkat inflasi. Hipotesis penelitian yaitu terdapat pertumbuhan ekonomi setiap tahunnya dikedua negara tersebut pasca krisis moneter.

The 2018 revision of the Consumer Price Index geographic sample

2016 ◽  
Author(s):  
Steven Paben ◽  
William Johnson ◽  
John Schilp
Keyword(s):  
Price Index ◽  
Consumer Price Index
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