Penggunaan Metode Backpropagation Pada Jaringan Syaraf Tiruan Untuk Intrusion Detection System


  • Ramli Ahmad Universitas Hamzanwadi
  • Bq Andriska Candra Permana Universitas Hamzanwadi
  • Amri Muliawan Nur Universitas Hamzanwadi



backpropagation network, IDS, deep learning, machine learning


Convenience is the main goal of existence of technology this days, but over time these technological advancements have made user privacy increasingly difficult and become a cause of concern. The existence of IDS (Intrusion Detection System ) is believed to help in achieving security in network usage where this detection system work by observing abnormal network behavior. IDS emphasizes the need to use artificial neural network to detect these attack. From the research tht has been done, the use of artificial neural network with a learning rate of 0.1 has been applied and the KDDCup-99 dataset has been used to train and make network benchmarks. To conduct a comparison, training has also been carried out on the same dataset using several other learning algorithms. The number of layer used in this artificial neural network start from 1 to 5, and the result have been compared so that the conclusion said that the artificial neural network with 3 layers has a superior performance compare to other machine learning algorithms.

DOI : 10.29408/jit.v3i2.2317


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How to Cite

Ahmad, R., Permana, B. A. C., & Nur, A. M. (2020). Penggunaan Metode Backpropagation Pada Jaringan Syaraf Tiruan Untuk Intrusion Detection System. Infotek: Jurnal Informatika Dan Teknologi, 3(2), 123–130.

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