Clustering Data Pelanggan Menggunakan K-Means untuk Segmentasi Pasar pada Sentra UMKM di Kota Banda Aceh
Abstract
Abstract
Segmentasi pasar merupakan elemen penting dalam merumuskan strategi pemasaran yang efektif, terutama bagi pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) yang ingin memperluas jangkauan pasar dan meningkatkan keterlibatan pelanggan. Penelitian ini bertujuan untuk menerapkan algoritma K-Means clustering dalam mengelompokkan data pelanggan dari sentra UMKM di Kota Banda Aceh ke dalam beberapa segmen pasar yang teridentifikasi. Data yang digunakan mencakup informasi demografis pelanggan, frekuensi pembelian, dan nilai transaksi, yang diperoleh melalui survei dan catatan penjualan dari beberapa sentra UMKM terpilih. Metode penelitian melibatkan tahapan preprocessing data, penentuan jumlah klaster optimal menggunakan Metode Elbow, serta proses clustering menggunakan algoritma K-Means. Hasil penelitian menunjukkan bahwa pelanggan dapat dikelompokkan secara efektif ke dalam beberapa segmen yang memiliki karakteristik berbeda, seperti pelanggan loyal dengan nilai transaksi tinggi, pelanggan sesekali yang sensitif terhadap harga, serta pelanggan baru dengan tingkat keterlibatan rendah. Temuan ini memberikan wawasan strategis bagi pelaku UMKM dalam merancang kampanye pemasaran yang lebih tepat sasaran, menyesuaikan penawaran produk, serta mengalokasikan sumber daya secara lebih efisien. Dengan memanfaatkan segmentasi berbasis data, UMKM di Banda Aceh dapat meningkatkan daya saing dan responsivitas terhadap kebutuhan pasar di era ekonomi digital.
Kata Kunci: K-Means, Clustering, Segmentasi Pasar, Data Pelanggan, UMKM, Banda Aceh
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