Model Combination of Activation Functions in Neural Network Algorithms (Case: Retail State Sukuk by Group)

Muhammad Noor Hasan Siregar

Abstract


This study aims to maximize the activation function used in backpropogation networks in finding the best architectural model. The case study used is the sale of state retail sukuk based on professional groups. The combination of activation functions used for training and testing is tansig-tansig, tansig-purelin and tansig logsig. The architectural model used is the architectural model 6-2-1 and 6-5-1. The evaluation parameters used are epoch, MSE training, MSE testing and accuracy level of truth. Data processing is assisted by using Matlab software. The results showed that the tansig-logsig activation function had more stable results than tansig-tansig and tansig-purelin.


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References


A. Sudarsono, “Jaringan Syaraf Tiruan Untuk Memprediksi Laju Pertumbuhan Penduduk Menggunakan Metode Bacpropagation (Studi Kasus Di Kota Bengkulu),” J. Media Infotama, vol. 12, no. 1, pp. 61–69, 2016.

T. Budiharjo, Soemartono, T., Windarto, A.P., Herawan, “Predicting school participation in indonesia using back-propagation algorithm model,” Int. J. Control Autom., 2018.

T. Budiharjo, Soemartono, T., Windarto, A.P., Herawan, “Predicting tuition fee payment problem using backpropagation neural network model,” Int. J. Adv. Sci. Technol., 2018.

R. Adistya and M. A. Muslim, “Deteksi dan Klasifikasi Kendaraan menggunakan Algoritma Backpropagation dan Sobel,” J. Mech. Eng. Mechatronics, vol. 1, no. 2, pp. 65–73, 2016.

A. P. Windarto, M. R. Lubis, and Solikhun, “Implementasi JST Pada Prediksi Total Laba Rugi Komprehensif Bank Umum Konvensional Dengan Backpropagation,” J. Teknol. Inf. dan Ilmu Komput., vol. 5, no. 4, pp. 411–418, 2018.

A. Trimulya, Syaifurrahman, and F. A. Setyaningsih, “Implementasi jaringan syaraf tiruan metode backpropagation untuk memprediksi harga saham,” J. Coding, Sist. Komput. Untan, vol. 3, no. 2, pp. 66–75, 2015.

Solikhun, A. P. Windarto, Handrizal, and M.Fauzan, “Jaringan Saraf Tiruan Dalam Memprediksi Sukuk Negara Ritel Berdasarkan Kelompok Profesi Dengan Backpropogation Dalam Mendorong Laju Pertumbuhan Ekonomi,” Kumpul. J. Ilmu Komput., vol. 4, no. 2, pp. 184–197, 2017.




DOI: https://doi.org/10.30645/ijistech.v2i2.23

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