PENGARUH JUMLAH HIDDEN LAYER DIDALAM ARSITEKTUR BACKPROPAGATION PADA ALGORITMA NEURO FUZZY TERHADAP PENDIAGNOSAAN BREAST CANCER WISCONSIN

HATI, DEVI PERMATA and Rini, Dian Palupi and Miraswan, Kanda Januar (2020) PENGARUH JUMLAH HIDDEN LAYER DIDALAM ARSITEKTUR BACKPROPAGATION PADA ALGORITMA NEURO FUZZY TERHADAP PENDIAGNOSAAN BREAST CANCER WISCONSIN. Undergraduate thesis, Sriwijaya University.

	Text RAMA_55201_09021181520030.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (2MB) | Request a copy
	Text RAMA_55201_09021181520030_TURNITIN.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (13MB) | Request a copy
Preview	Text RAMA_55201_09021181520030_0023027804_0009019002_01_front_ref.pdf - Accepted Version Available under License Creative Commons Public Domain Dedication. Download (544kB) | Preview
	Text RAMA_55201_09021181520030_0023027804_0009019002_02.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (373kB) | Request a copy
	Text RAMA_55201_09021181520030_0023027804_0009019002_03.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (577kB) | Request a copy
	Text RAMA_55201_09021181520030_0023027804_0009019002_04.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (888kB) | Request a copy
	Text RAMA_55201_09021181520030_0023027804_0009019002_05.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (121kB) | Request a copy
	Text RAMA_55201_09021181520030_0023027804_0009019002_06.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (33kB) | Request a copy
	Text RAMA_55201_09021181520030_0023027804_0009019002_07_ref.pdf - Bibliography Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (97kB) | Request a copy
	Text RAMA_55201_09021181520030_0023027804_0009019002_08_lamp.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Public Domain Dedication. Download (247kB) | Request a copy

Abstract

The Backpropagation algorithm has a weakness in processing data directly from the experience of experts without knowing the tendency to enter the target. Fuzzy Logic is the right choice in overcoming this, because the function of fuzzy logic is to create a degree of membership where the value of a higher degree of membership in a target can indicate that the data will enter the target. The effect of the number of hidden layers on the results of the training test can be known by looking at the error value. The smaller the error value, the better the accuracy will be. So the results of the study in comparing the effect of the number of hidden layers in the backpropagation architecture on the Neuro Fuzzy algorithm for the diagnosis of Breast Cancer Wisconsin, resulted in different accuracy, where the application of 2 hidden layers resulted in a better accuracy rate of 93.66% while the application of 1 hidden layer resulted in accuracy. by 91.22%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Neural Network, Breast Cancer Wisconsin, Backpropagation, Fuzzy Logic, Hybrid Computational Intelligence.
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General) T Technology > T Technology (General) > T57.6-57.97 Operations research. Systems analysis > T57.6.A2-Z General works Simulation Cf. QA76.9.C65 Computer science Cf. TA343 Engineering mathematics
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	DEVI PERMATA HATI
Date Deposited:	29 Jul 2021 07:09
Last Modified:	29 Jul 2021 07:09
URI:	http://repository.unsri.ac.id/id/eprint/50927

Actions (login required)

View Item