Skripsi

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

---

Penilaian

---

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%.

---

Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002672	T50927	T509272021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

-

Call Number

T509272021

Publisher

Inderalaya : Prodi Teknik Informatika, Fakultas Ilmu komputerv., 2021

Collation

xvii, 127 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

-

Classification

004.07

Content Type

Text

Media Type

-

Carrier Type

-

Edition

-

Subject(s)

Pemrosesan Data, Teknik Informatika
Prodi Teknik Informatika

Specific Detail Info

-

Statement of Responsibility

MURZ

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment