Skripsi

OPTIMASI ALGORITMA DECISION TREE MENGGUNAKAN METODE ARTIFICIAL BEE COLONY UNTUK KLASIFIKASI DATA PENDERITA PENYAKIT DIABETES

---

Penilaian

---

Diabetes is a long-term or chronic disease. Diabetes can attack anyone and under any conditions and will continue for a lifetime. In reality, most diabetes is predicted too late, causing complications with other diseases which will ultimately lead to death. This system is expected to be able to alert the risk of complications in diabetes patients in the future. Extract knowledge from diabetes data with machine learning to learn patterns. This research tests the effect of Decision Tree C4.5 optimization for classification with Artificial Bee Colony for selecting data attributes to be used. Classification using the Decision Tree C4.5 algorithm produces an accuracy of 0.74. Meanwhile, after selecting the Artificial Bee Colony feature, it produced an accuracy value of 0.77. The increase in classification accuracy reached 0.03. Optimization using the Artificial Bee Colony method succeeded in increasing the accuracy of the Decision Tree C4.5 algorithm in classification diabetes data.

---

Availability

Inventory Code	Barcode	Call Number	Location	Status
2407003992	T149449	T1494492024	Central Library (REFERENCES)	Available but not for loan - Not for Loan

Detail Information

Series Title

-

Call Number

T1494492024

Publisher

Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer., 2024

Collation

xvii, VI-2 hlm.; ilus.; tab.; 28 cm

Language

Indonesia

ISBN/ISSN

-

Classification

518.107

Content Type

Text

Media Type

unmediated

Carrier Type

unspecified

Edition

-

Subject(s)

Prodi Teknik Informatika
Algoritma Decision Tree

Specific Detail Info

-

Statement of Responsibility

UIN Farrah

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment