KLASIFIKASI DIAGNOSIS PENYAKIT STROKE DENGAN MENGGUNAKAN METODE RANDOM FOREST

Nur Aliffiyanti Iskandar, . (2022) KLASIFIKASI DIAGNOSIS PENYAKIT STROKE DENGAN MENGGUNAKAN METODE RANDOM FOREST. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Stroke is the second leading cause of death and third disability in the world, where 70% of stroke patients occur in low- and middle-income countries. Meanwhile, death and disability caused by stroke accounted for 87%. Stroke and TIA (Transient Ischemic Attack) are included in emergency cases. However, early symptoms of stroke are difficult to know. Data mining can be used to diagnose diseases. The aim of this research is to get the best model using Random Forest for stroke. The model using 90 trees produces the optimal value, where the accuracy value is 95.2%, sensitivity is 4.1%, specificity is 99.8%, precision is 66.7%, and F-measure is 7.6%. And ROC Curve of 0.8048 which indicates that the model is included in the Good Classification.

Item Type:	Thesis (Skripsi)
Additional Information:	{No Panggil: 1810511002} {Pembimbing 1: Iin Ernawati] [Pembimbing 2: Yuni Widiastiwi] [Penguji 1: Jayanta] {Penguji 2: Nurul Chamidah]
Uncontrolled Keywords:	Classification, Random Forest, Stroke
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TN Mining engineering. Metallurgy
Divisions:	Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User:	Nur Aliffiyanti Iskandar
Date Deposited:	19 Aug 2022 02:30
Last Modified:	19 Aug 2022 02:30
URI:	http://repository.upnvj.ac.id/id/eprint/19717

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