Pemodelan Prediksi Pendapatan Individu sebagai Strategi Analitik Ekonomi Berbasis Data Census-Income (KDD)
DOI:
https://doi.org/10.54342/57mszs92Keywords:
Business Analytics, Data Sensus, Prediksi PendapatanAbstract
Penelitian ini menerapkan analisis business analytics untuk memprediksi pendapatan individu berdasarkan data sensus Census-Income (KDD) dari UCI Machine Learning Repository. Dataset mencakup 199.523 data individu dari wilayah Los Angeles dan Long Beach selama tiga periode sensus: 1970, 1980, dan 1990. Penelitian menggunakan algoritma Gaussian Naïve Bayes dengan pembagian data sebesar 80% untuk pelatihan dan 20% untuk pengujian. Proses mencakup preprocessing, eksplorasi statistik, pemodelan, dan evaluasi. Hasil menunjukkan akurasi klasifikasi sebesar 84,7%, dengan nilai precision 0,82 dan recall 0,85. Visualisasi data dilakukan menggunakan histogram, scatter plot, dan heatmap. Penelitian ini memberikan kontribusi dalam membangun model prediktif berbasis data demografis, serta menjadi dasar dalam perumusan kebijakan sosial-ekonomi yang lebih inklusif dan berbasis bukti.
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