http://dspace-surabaya.uph.edu:8080/xmlui/handle/123456789/892 Fri, 06 Nov 2026 14:46:38 GMT 2026-11-06T14:46:38Z http://dspace-surabaya.uph.edu:8080/xmlui/handle/123456789/901 Optimasi Conjugate Gradient Pada Algoritma Backpropagation Neural Network Untuk Prediksi Kurs Time Series Sari, Yuslena This paper investigates the use of methods of propagation neural network to forecast the rupiah against the dollar in time series . Data is divided into two parts , namely the training data test data . Having obtained the best weight training results data then after that test data is used to see the results of MSE . Training algorithm uses basic backpropagation gradient descent algorithm and then optimized using the conjugate gradient . The results show the value of the basic algorithm backpropogation MSE gradient descent and conjugate gradient of 1.02159 mengsilkan MSE of 0.0198012 . From these results indicate conjugate gradient algorithm produces smaller error. Wed, 01 Jun 2016 00:00:00 GMT http://dspace-surabaya.uph.edu:8080/xmlui/handle/123456789/901 2016-06-01T00:00:00Z http://dspace-surabaya.uph.edu:8080/xmlui/handle/123456789/900 Implementasi FMCDM Sebagai Alternatif Penentuan Dalam Pemilihan Lokasi Perumahan Salim, Yeffiansjah Decision making system implementation the optimal with several criteria using fuzzy multi- criteria decision-making(FMCDM) used to review completed decision to 7 ( seven ) criteria will become material considerations fmcdm as the highest priority as an optimal alternative highest, singer systems provide housing location with options until highest priority the lowest location with desire accordance housing development prospective homebuyers the optimal based on criteria with regard value total integral the tin , the big value total integram shows that alternative high more match rate based criteria. Wed, 01 Jun 2016 00:00:00 GMT http://dspace-surabaya.uph.edu:8080/xmlui/handle/123456789/900 2016-06-01T00:00:00Z http://dspace-surabaya.uph.edu:8080/xmlui/handle/123456789/899 Optimasi PSO Untuk Peramalan Harga Emas Secara Rentet Waktu Mukhlis, Iwan Fitriadi PSO is one of the best methods of AI techniques for optimization and parameter estimation . Emad et al , in the study presented a comparison between the five -based optimization algorithm AI recently , namely : GA , mathematics algorithm , particle swarm optimazition , ant -colony systems , and shuffled frog . The comparison showed that the PSO is one that has algorithms that provide a solution with success rates and better quality . In this study the model rentet time PSO -based forecasting gold prices proposed using PSO algorithms for parameter estimation . Forecasting the price of gold , in terms of input , will be discussed with the use of time lags behind the price of gold as an input Wed, 01 Jun 2016 00:00:00 GMT http://dspace-surabaya.uph.edu:8080/xmlui/handle/123456789/899 2016-06-01T00:00:00Z http://dspace-surabaya.uph.edu:8080/xmlui/handle/123456789/898 Prediksi Harga Saham Menggunakan Neural Network Hidayat, Rahmat One of the central economic movements Bursa Efek Indonesia (BEI) and IDX every day trade the company's stock exchanges, the overall movement of the stock. One sector that is in IDX and IDX is the mining sector, which is a company related to the mine or komoditas. Hal can also affect the company's stock price and a positive influence on the Indeks Harga Saham Gabungan(IHSG) movement. With the prediction of stock price, it is very helpful to investors in decision making. In addition to predicting the conventional methods can also be used in the Neural Network (Artificial Neural Network). A neural network makes predictions based on the input descriptor variables are presented to the network and the associated weights dijaringan connection. In the prediction using neural netwok there are several algorithms that are often used as propagation and optimization with conjugate gradient. The algorithm predicts using training data set by adjusting the weights to reduce the prediction error. Wed, 01 Jun 2016 00:00:00 GMT http://dspace-surabaya.uph.edu:8080/xmlui/handle/123456789/898 2016-06-01T00:00:00Z