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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Nyimas Ayu Widi Indriana
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Momentum Backpropagation Untuk Klasifikasi Fungsi Senyawa Aktif Berdasarkan Notasi SMILES (Simplified Molecular Input Line Entry System) Nyimas Ayu Widi Indriana; Dian Eka Ratnawati; Syaiful Anam
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Active compounds can be used to make certain drugs and very important in the medical sector. Classification of active compounds is the most important thing in making medicines. After classifying the active compound, it is continued with the process of making and testing drugs that require a variety of tools. The cost of making and testing these drugs requires a high cost and time. This is a major obstacle for medical experts to make certain medicines. By utilizing current technology, a system can be made to classification process of active compounds, so the performance of medical experts for making certain drugs can be faster. The classification process can be done by using a computer and utilizing the SMILES notation. SMILES notation allows a compound to be processed by a computer. The momentum Backpropagation method can be used to perform the classification process properly. Based on the program that has been made, there are 4 types of testing using 522 training data and 131 test data producing, the best accuracy of 70,99% with a learning rate of 0,00001, max epoch of 100, momentum of 0,25 and hidden layer neurons of 4.
Co-Authors Anam, Syaiful Dian Eka Ratnawati