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Salman, Afan Galih
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Computer Science & IT Engineering Mathematics

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Aplikasi Wisata Berplatform Android dengan Teknologi QR Code Salman, Afan Galih
ComTech: Computer, Mathematics and Engineering Applications Vol 4, No 2 (2013): ComTech
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/comtech.v4i2.2502

Abstract

As a country renowned for its natural beauty, Indonesia has many interesting attractions to visit. An example is the attraction of animals shown at Ragunan Zoo. At Ragunan Zoo visitors not only enjoy the tour, but also learn about animals shown. However, information about the animals is only provided on the board. Therefore,Ragunan Zoo needs a technology that provides more information, efficiently and as a guide to explore the tourist attractions. The purpose of this research is to design an android-based mobile application that can provide information more than what is show on the board as well as provides digital mapinformation. The application generated in this study implements the QR code scanning to obtain information as well as locations of digital map attraction.
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 Prasetio, Yen Lina