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All Journal Journal of Mathematical and Fundamental Sciences Journal of Engineering and Technological Sciences Indonesia Symposium on Computing KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Desimal: Jurnal Matematika Limits: Journal of Mathematics and Its Applications Journal of Research in Mathematics Trends and Technology Jurnal Teknik Informatika (JUTIF) MATHunesa: Jurnal Ilmiah Matematika Jurnal Siger Matematika Jurnal Matematika Integratif
Aang Nuryaman
Universitas Lampung
Astronomy Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation

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Journal : KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal)

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IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK (ANN) USING BACKPROPAGATION ALGORITHM BY COMPARING FOUR ACTIVATION FUNCTIONS IN PREDICTING GOLD PRICES Dian Kurniasari; Ranti Vidia Mahyunis; Warsono Warsono; Aang Nuryaman
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 10, No 1 (2023)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v10i1.587

Abstract

The trend in global currency values is speedy and fluctuating due to the recession caused by the Covid-19 pandemic. That causes investors to flock to buy gold assets. Therefore, it is necessary to predict the price of gold from a business and academic perspective to obtain a reasonable gold price prediction model. This study applies the Backpropagation Algorithm by determining the best ANN model structure based on four activation functions: Sigmoid, Tanh, ReLU, and Linear, as well as learning rate values, namely 0.01 and 0.001. The results are the best ANN model structure with four nodes in the input layer, four nodes in the hidden layer and the output layer using the Linear activation function and a learning rate of 0.01. Based on the structure of the model, the MSE value is 0.00051, the MAPE value is 1.9798%, and the accuracy is 98%.Keywords: Artificial Neural Network, Backpropagation, Gold Price Prediction, Activation Function, Model Structure Trend nilai mata uang global sangat cepat dan fluktuatif akibat terjadinya resesi yang disebabkan oleh pandemi Covid-19. Hal ini menyebabkan, para investor berbondong-bondong untuk membeli aset emas. Oleh sebab itu, perlu dilakukan prediksi harga emas, baik dari perspektif bisnis maupun akademis agar memperoleh model prediksi harga emas yang baik. Penelitian ini menerapkan Algoritma Backpropagation dengan menentukan struktur model ANN terbaik berdasarkan empat fungsi aktivasi yaitu, Sigmoid, Tanh, ReLU, dan Linear serta nilai learning rate, yaitu 0,01 dan 0,001. Hasil yang diperoleh berupa struktur model ANN terbaik dengan empat node pada input layer, empat node pada hidden layer dan output layer dengan menggunakan fungsi aktivasi Linear dan learning rate sebesar 0,01. Berdasarkan struktur model tersebut, diperoleh nilai MSE sebesar 0.00051, nilai MAPE sebesar 1,9798% dan akurasi sebesar 98%.Kata Kunci: Artificial Neural Network, Backpropagation, Prediksi Harga Emas, Fungsi Aktivasi, Struktur Model
Co-Authors . Wamiliana Agus Yodi Gunawan Ahmad Faisol Ahmad Faisol Ahmad Rizki Wiranto Asmiati Asmiati Asmiati Asmiati Atika Faradilla Bagus Hayatul Jihad Bagus Hayatul Jihad Citra Puspa Tria Dalfa Habibah Nurul Aini Dewi Rakhmatia Nur Dian Kurniasari Dina Eka Nurvazly Eri Setiawan Eri Setiawan Fathudin Fathudin Ismawati Ismawati Kuntjoro Adji Sidarto La Zakaria La Zakaria Mega Putri Muhammad Ihsan Abyan Muhammad Ihsan Abyan Mustofa Usman Mustofa Usman Nabilla Yolanda Paramitha Notiragayu Notiragayu Ranti Vidia Mahyunis Raratia ulsa Alfian Rudi Ruswandi Saidi, Subian Saiful Rohman Soleh Fajar Junjunan Soleh Fajar Junjunan Warsono Warsono Warsono Warsono Widiarti Widiarti Yogi Wibisono Budhi