Analisa dan Komparasi 5 Algoritma Klasifikasi untuk Penduduk Miskin berdasarkan Usia dan Jenis Kelamin

Munawir Hamzah

doi:10.54066/jci.v1i1.212

Munawir Hamzah Akademi Komunitas BPPMNU Banat Kudus

DOI: https://doi.org/10.54066/jci.v1i1.212

Keywords: Komparasi, Algoritma, Decision Tree, Naive Bayes, K-Nearest Neighbor, Random Tree, Random Forest, T-Test

Abstract

Kemiskinan adalah berbeda-beda dan merefleksikan suatu spektrum orientasi ideologi. Faktor yang mempengaruhi tingkat kemiskinan adalah pertumbuhan ekonomi. Jadi kemiskinan tidak lagi sekedar masalah kekurangan makanan saja. Pertumbuhan keseluruh sektor usaha sangat dibutuhkan dalam upaya menurunkan tingkat kemiskinan. Untuk menangani dan berkoordinasi dalam hal-hal yang berkaitan dengan penanggulangan kemiskinan, maka perlu mengklasifikasikan usia dan jenis kelamin dari individu dengan tingkat kesejahteraan 30% terbawah. Seiring dengan perkembangan teknologi yang begitu pesat, perkembangan algoritma komputer sedang mengembangkan beberapa algoritma untuk mendukung kemajuan sistem komputerisasi. Algoritma yang terkenal diantaranya adalah algoritma Decision Tree (C4.5), Random Tree, Linear and Quadratic Discriminant Analysis, Neural Network, Least Square Support Vector Machines, K-NN, Random Forest, CART, dan Naive Bayes.

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