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Prasetio, Yen Lina
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Computer Science & IT Engineering Mathematics

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Aplikasi Perangkat Ajar Kebudayaan Indonesia Berbasis Multimedia Halim, Adriani; S. A., Yunair Octaarianti Octaarianti; Yosanny, Agustinna; Prasetio, Yen Lina
ComTech: Computer, Mathematics and Engineering Applications Vol 3, No 1 (2012): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v3i1.2458

Abstract

The purpose of this research is to design a CAI application as a learning support and media to introduce the valuable cultures of Indonesia. The CAI is objected to children or people using computer. The research applied the Interactive Multimedia System Design & Development (IMSDD) method, which consists of system requirement, design consideration, implementation, and evaluation. The result of this research is a CAI application about Indonesian culture based on multimedia that fulfills the user?s need on CAI application. CAI is expected to grow users? interest about Indonesian culture, improve children?s memory capability, and help create the learning process more interesting and fun.
Implementasi Jaringan Syaraf Tiruan Recurrent Menggunakan Gradient Descent Adaptive Learning Rate and Momentum Untuk Pendugaan Curah Hujan Salman, Afan Galih; Prasetio, Yen Lina
ComTech: Computer, Mathematics and Engineering Applications Vol 2, No 1 (2011): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v2i1.2707

Abstract

The artificial neural network (ANN) technology in rainfall prediction can be done using the learning approach. The ANN prediction accuracy is measured by the determination coefficient (R2) and root mean square error (RMSE). This research implements Elman?s Recurrent ANN which is heuristically optimized based on el-nino southern oscilation (ENSO) variables: wind, southern oscillation index (SOI), sea surface temperatur (SST) dan outgoing long wave radiation (OLR) to forecast regional monthly rainfall in Bongan Bali. The heuristic learning optimization done is basically a performance development of standard gradient descent learning algorithm into training algorithms: gradient descent momentum and adaptive learning rate. The patterns of input data affect the performance of Recurrent Elman neural network in estimation process. The first data group that is 75% training data and 25% testing data produce the maximum R2 leap 74,6% while the second data group that is 50% training data and 50% testing data produce the maximum R2 leap 49,8%.
Co-Authors Halim, Adriani S. A., Yunair Octaarianti Octaarianti Salman, Afan Galih Yosanny, Agustinna