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Bayu Rahayudi
Fakultas Ilmu Komputer , Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Identifikasi Penyimpangan Tumbuh Kembang Anak Dengan Algoritme Backpropagation Fadhilla Puji Cahyani; Muhammad Tanzil Furqon; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 5 (2018): Mei 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Growth and development are two processes that are interdependent and inseparable. Growth and development of children greatly affect the quality of growth and development of children in the future. In the development phase, often encountered irregularities that cause delay in child development when compared to children of the same age. Developmental disorders that often occurred in children are such as autism, Attention Deficit Disorder (ADHD), and Down Syndrome. This study aims to identify the type of development disorder of children based on symptoms that appear using Backpropagation algorithm. Backpropagation algorithm is one of Artificial Neural Network algorithm that has ability to solve complex problems that can not be solved by conventional learning technique. The network architectures used in this study are 38 input neurons, 5 hidden neurons, and 3 output neurons. The results of this study indicate that Backpropagation algorithm can identify the development disorder of children well with the average accuracy of 91,11% in the test of training data of 81, 9 testing data, learning rate 0,1, and 0,0009 minimun error.
Implementasi Metode Certainty Factor pada Identifikasi Kerusakan Kendaraan Bermotor Roda Dua Gaung Rimba Putra Dirgantara; Suprapto Suprapto; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 6 (2018): Juni 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The purpose of this study is to help motorcycle riders and mechanics to identify the breakdowns of motorcycle based on symptoms. Limited number of experts to repair the motorcycles will spend long time to identify and repair the motorcycles. Hence, this study is done to make an application system to identify the breakdowns of motorcycle with Certainty Factor methods. The evaluation of this study use the testing scenario that compare the value of accuracy from the result of the expert questionnaires with application system. On the test, obtained the value of accuracy that is pretty good with 73,3%. This value proves that this study still have opportunities to be developed even further.
Co-Authors Fadhilla Puji Cahyani Gaung Rimba Putra Dirgantara Muhammad Tanzil Furqon Supraptoa Supraptoa