OPTIMASI ALGORITMA RANDOM FOREST MENGGUNAKAN ALGORITMA GENETIKA DALAM PROSES KLASIFIKASI PENYAKIT GINJAL KRONIS

AMANDA, VIRANI and Rini, Dian Palupi and Utami, Alvi Syahrini (2023) OPTIMASI ALGORITMA RANDOM FOREST MENGGUNAKAN ALGORITMA GENETIKA DALAM PROSES KLASIFIKASI PENYAKIT GINJAL KRONIS. Undergraduate thesis, Sriwijaya University.

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Abstract

Chronic kidney disease is a global public health problem with a high incidence rate. About one-tenth of the world's population suffers from this disease. The high number of sufferers is accompanied by the need for proper diagnosis. Classification is one of the methods that can be used to diagnose chronic kidney disease quickly. And Random Forest is a Classification method that can produce high accuracy. This study used 40 data with 20 features consisting of blood pressure, albumin, sugar, and others. Because the data used has many features, a Genetic Algorithm is used to select these features. This study aims to optimize the Random Forest method using the Genetic Algorithm in Classification, as well as compare the performance of the Random Forest method with optimization and the Random Forest method without optimization. The test results show that the Random Forest method without being optimized produces an accuracy of 80%. While the optimized Random Forest method has greater accuracy, namely, 90% even though it requires a longer computational time and uses a lot of memory.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Ginjal Kronis, Random Forest, Algoritma Genetika, Akurasi
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Virani Amanda
Date Deposited:	24 Jan 2023 03:27
Last Modified:	24 Jan 2023 03:28
URI:	http://repository.unsri.ac.id/id/eprint/87363

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