Perbandingan Algoritma K-Nearest Neighbor (K-NN) dan Naive Bayes dalam Klasifikasi Tingkat Kemiskinan di Indonesia - Juanuari Juanuari; Maulana Ilyas; Rahmat Tri Widodo; Ilham Manzis; Yusnia Budiarti; Musriatun Napiah (IAI Nasional Laa Roiba Bogor, 2026)
Poverty is a major issue in sustainable development in Indonesia that requires a data-driven analysis approach to produce more accurate identification. This study aims to compare the performance of the K-Nearest Neighbor (K-NN) and Naive Bayes algorithms in classifying poverty levels in Indonesia based on social and economic data. The dataset was obtained from the Kaggle platform with the title