Nururrohman, M. Tsalits and Hapsari, Dian Puspita and Utungga, Reza (2015) RANCANG BANGUN APLIKASI DIAGNOSA KERUSAKAN KOMPUTER DENGAN METODE BACKPROPAGATION. Networking Engineering Research Operation [NERO], Vol 1, (3). pp. 212-221. ISSN 2355-2190

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Computer damage is a problem requiring an intervention by a technician to fix it. However, a technician sometimes is wrong in diagnosing the damage and even takes longer time to do so. This is specifically due to the level of his knowledge, skill and experience. In order to cope with such problem, it requires a web-based application for diagnosing damages in computers by means of a backpropagation method. Initially each complaint on the damage is classified into a binary pattern. Next, based on the binary pattern, the damaged is identified. The application then goes on trial for sometimes until the Artificial Neural Network can identify the training pattern in compliance with the target. The results of the research analysis showed that the Artificial Neural Network with backpropagation method is an information processing system for network exercising to attain a balance between the ability of the network to identify the adopted pattern during the exercise and the ability of the network to give correct responses to patterns of input similar the ones used in the network exercising. The results of 20 predictive tests showed that the application could predict the problem accurately by 100%. On the other hands, the accuracy of the of manual prediction was 75%. In conclusion, the output of each Artificial Neural Network was adoptable as a consideration by a technician to take decision to cope with the computer problem. Keyword : computer damage, Artifical Neural Network, backpropagation

Item Type: Article
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
Divisions: Fakultas Matematika dan Ilmu Pengetahuan Alam > Matematika
Depositing User: salis nurur rohman
Date Deposited: 14 Mar 2019 02:40
Last Modified: 14 Mar 2019 02:40
URI: http://repository.unisda.ac.id/id/eprint/18

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