CD Skripsi

Perbandingan Algoritma Random Forest Dan Decision Tree Untuk Klasifikasi Rumah Tangga Miskin Di Pekanbaru Tahun 2020

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ABSTRACT
Poverty is a condition of a person's inability to meet the standard of basic necessities of life. Poverty is one of the indicators of people's welfare that determines the condition of welfare and the success of development in a country. The study aims to classify poor households in Pekanbaru City in 2020 with a total of 797 households. The classification algorithms used are random forest and decision tree. This study shows that the random forest algorithm produced accuracy, sensitivity, specificity, precision, and f1-score values of 83,4%, 84,2%, 57,1%, 98,5%, and 90,8%, respectively. The decision tree algorithm produces an accuracy value of 76,2%, 75,9%, 85,7%, 99,4%, and 86,1%, respectively. This proves that the random forest algorithm is the best algorithm in classifying poor households in Pekanbaru City in 2020.
Keywords: Poverty, classification, random forest, decision tree

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

190315654

Penerbit

Pekanbaru : Universitas Riau – FMIPA – STATISTIKA., 2023

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

190315654

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

STATISTIKA

Info Detail Spesifik

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Pernyataan Tanggungjawab

PUJA

Versi lain/terkait

Lampiran Berkas

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