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Herlambang, Teguh -
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Prediksi Harga Saham pada PT. ABCD menggunakan Ensemble Kalman Filter Katias, Puspandam; Fidita, Denis; Herlambang, Teguh -
Zeta - Math Journal Vol 4 No 1 (2018): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (257.916 KB) | DOI: 10.31102/zeta.2018.4.1.24-27

Abstract

Stock Exchange is established as an effort to link both stock / security sellers and buyers. Securities often traded in stock market is share. The intention of an investor in investment is to have the lowest risk and to gain the highest profit. To make decision for optimal investment, calculation on the estimate of future return to be gained is necessarily made. One of estimate calculation methods considered the most objective is by applying the Ensemble Kalman filter (EnKF) method. Ensemble Kalman filter is a method of estimation of condition variable of discrete linear dynamic system that minimizes covarian error of estimation. So, this study aims to apply share price estimation method for close prices of share of PT. ABCD by Ensemble Kalman Filter method as investor' consideration in investment with an error of 3% - 5%.
Peramalan Kebutuhan Darah Jenis Packet Red Cells (PRC) di PMI Kota Surabaya dengan Metode Jaringan Syaraf Tiruan Propagasi Balik Devi, Azmi Khulmala; Herlambang, Teguh -
Zeta - Math Journal Vol 4 No 1 (2018): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (372.428 KB) | DOI: 10.31102/zeta.2018.4.1.7-11

Abstract

Human blood is liquid in human body, which functions to transport oxigen needed by cells to the whole body. Considering the important blood function, the Indonesian Red Cross (PMI) has to maintain its blood stock stability to ensure the blood availibility. But the problem that PMI has to encounter with is its blood over-supply which leads to blood disposal. To minimize its unnessary blood disposal, estimation of blood need is required. Data of blood demand is normalized first, then estimation is made using Neural Network Backpropagation. In this study the estimation is made to the blood type of Packet Red Cells (PRC), the blood cells stocked at PMI Kota Surabaya. The best simulation result is at epoch 3000 with function Y = 4542,33 – 1,64595 x – 0,244018 x^2 and an error of 0,020314.
Co-Authors Devi, Azmi Khulmala Fidita, Denis Puspandam Katias