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

ANDRIANI, DINI and Rini, Dian Palupi (2024) OPTIMASI ALGORITMA DECISION TREE MENGGUNAKAN METODE ARTIFICIAL BEE COLONY UNTUK KLASIFIKASI DATA PENDERITA PENYAKIT DIABETES. Undergraduate thesis, Sriwijaya University.

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Abstract

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.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Klasifikasi, Decision Tree C4.5, Artificial Bee Colony, Seleksi Fitur, Penyakit Diabetes
Subjects:	T Technology > T Technology (General) > T59.4 Mechanization
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Dini Andriani
Date Deposited:	05 Jul 2024 04:03
Last Modified:	05 Jul 2024 04:03
URI:	http://repository.unsri.ac.id/id/eprint/149449

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