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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Journal of Computer and Information Systems Ampera
Miftahul Falah
Universitas Sriwijaya, Palembang
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Kombinasi Algoritma Backpropagation Neural Network dengan Gravitational Search Algorithm Dalam Meningkatkan Akurasi Miftahul Falah; Dian Palupi Rini; Iwan Pahendra
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2597

Abstract

Predicting disease is usually done based on the experience and knowledge of the doctor. Diagnosis of such a disease is traditionally less effective. The development of medical diagnosis based on machine learning in terms of disease prediction provides a more accurate diagnosis than the traditional way. In terms of predicting disease can use artificial neural networks. The artificial neural network consists of various algorithms, one of which is the Backpropagation Algorithm. In this paper it is proposed that disease prediction systems use the Backpropagation algorithm. Backpropagation algorithms are often used in disease prediction, but the Backpropagation algorithm has a slight drawback that tends to take a long time in obtaining optimum accuracy values. Therefore, a combination of algorithms can overcome the shortcomings of the Backpropagation algorithm by using the success of the Gravitational Search Algorithm (GSA) algorithm, which can overcome the slow convergence and local minimum problems contained in the Backpropagation algorithm. So the authors propose to combine the Backpropagation algorithm using the Gravitational Search Algorithm (GSA) in hopes of improving accuracy results better than using only the Backpropagation algorithm. The results resulted in a higher level of accuracy with the same number of iterations than using Backpropagation only. Can be seen in the first trial of breast cancer data with parameters namely hidden layer 5, learning rate of 2 and iteration as much as 5000 resulting in accuracy of 99.3 % with error 0.7% on Backpropagation Algorithm, while in combination BP & GSA got accuracy of 99.68 % with error of 0.32%.
Perancangan Sistem Informasi dan Analisis Penjualan Depot Galon dengan Proses RO Berbasis Web Menggunakan Metode Incremental Dina Zalfa Khairunnisa; Miftahul Falah; Aulia Vandera; Zulaikha Savira Viwinanda; Muhammad Daffa Fathurrahman; Fajar Rizky Septian
Journal of Computer and Information Systems Ampera Vol. 7 No. 2 (2026): Journal of Computer and Information Systems Ampera
Publisher : APTIKOM SUMSEL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalcisa.v7i2.751

Abstract

The rapid development of digital technology has increased the importance of information systems in supporting business operations, including the drinking water refill industry. Asy Barokah, a refill service utilizing Reverse Osmosis (RO) technology, faces several challenges such as limited promotional activities, manual transaction recording, and inefficient communication with customers. This study aims to develop a web-based information system that improves promotional effectiveness, streamlines sales recording, and enhances operational management. The system was built using the Incremental method, allowing prioritized features to be implemented in stages. The resulting system provides a business profile page, digital promotion tools, online ordering, financial recording automation, and integrated operational management. The implementation demonstrates that the system effectively improves data accuracy, operational efficiency, and the quality of customer interactions. Overall, the developed system supports a more structured, responsive, and professional business process.
Co-Authors Aulia Vandera Dian Palupi Rini Dina Zalfa Khairunnisa Fajar Rizky Septian Iwan Pahendra Muhammad Daffa Fathurrahman Zulaikha Savira Viwinanda