DIAGNOSA PENYAKIT DIABETES MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION LEVENBERG-MARQUARDT

JUPANDI, RUBEN and Rini, Dian Palupi and Rodiah, Desty (2020) DIAGNOSA PENYAKIT DIABETES MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION LEVENBERG-MARQUARDT. Undergraduate thesis, Sriwijaya University.

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Abstract

Diabetes is a condition caused by an increase in glucose or sugar levels in the blood. Diabetes cannot be cured, but with proper control, organ failure and tissue damage can be prevented. In response to this condition, early detection of diabetes needs to be done by developing software for diabetes diagnosis using artificial neural networks. The most commonly used algorithm is backpropagation. However, this algorithm takes a longer time to reach convergence, therefore optimization is needed. This study succeeded in developing a software for diabetes diagnosis using levenberg-marquardt-optimized backpropagation. Testing using 4 maximum iterations and 5 learning rates, Backpropagation levenberg-marquardt produces optimal performance using a learning rate of 0.3 and a maximum of 500 iterations with an accuracy of 86.23% and an f-measure of 80.61%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Pembelajaran Mesin
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 9848 not found.
Date Deposited:	18 Jan 2021 03:41
Last Modified:	18 Jan 2021 03:41
URI:	http://repository.unsri.ac.id/id/eprint/39933

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