Implementasi Algoritma C.45 dalam Klasifikasi Kondisi Ekonomi Warga Kabupaten Boyolali: (Studi Kasus Desa Sumbung Kecamatan Cepogo) - Prasetyo, Andhi; Wahyono, Ari (Universitas Nusantara PGRI Kediri, 2024)
The economic impact following the Covid-19 pandemic has been felt by various countries. The Indonesian government is implementing economic recovery and providing social assistance based on economic conditions, but there are still residents who do not receive assistance but deserve help. The Sumbung Village Government is trying to anticipate by looking for indicators that influence economic conditions.The research was carried out using the Data Mining classification method. uses the C4.5 Algorithm because it produces decision tree visualizations that are easy to understand. The data used is Boyolali MCD data for Sumbung Village, Cepogo District. As a result of the analysis of 21 attributes, 8 criteria with the highest weight for indicators of economic conditions. The accuracy reached 94.47%, higher than Naïve Bayes (93.28%) and K-NN (91.70%), making it suitable for classifying the economic conditions of Boyolali Regency residents, especially Sumbung Village.