Penerapan K-Means Clustering untuk Segmentasi Data Penjualan Toko Aksesoris Komputer Menggunakan Google Colab
DOI:
https://doi.org/10.38035/dit.v3i3.3572Keywords:
Business Intelligence, Analitik Data, Google Colab, K-Means Clustering, Pengambilan Keputusan BisnisAbstract
Pengelolaan data penjualan secara efektif merupakan kebutuhan mendasar bagi pelaku usaha di era digital. Penelitian ini bertujuan menganalisis data penjualan toko aksesoris komputer menggunakan Google Colaboratory (Colab) berbasis data Microsoft Excel sebagai sarana pendukung pengambilan keputusan bisnis berbasis data. Data yang digunakan merupakan data transaksi dummy yang merepresentasikan 120 transaksi penjualan dengan sepuluh variabel, meliputi ID pelanggan, usia, gender, produk, kategori produk, harga, jumlah beli, total belanja, frekuensi belanja, dan waktu belanja. Metodologi penelitian mencakup statistik deskriptif, analisis produk terlaris, analisis perilaku konsumen berdasarkan gender dan waktu belanja, analisis scatter plot hubungan frekuensi dan total belanja, serta segmentasi pelanggan menggunakan K-Means Clustering dengan tiga cluster optimal. Hasil menunjukkan Headset Gaming merupakan produk terlaris (22 transaksi, 18,3%), diikuti Laptop Acer dan Printer Epson (16 transaksi). Kategori Aksesoris mendominasi dengan 42 transaksi (35,0%). Pelanggan laki-laki berkontribusi 66,1% dari total belanja (Rp38.490.000). Waktu belanja terbanyak pada siang hari (32,5%). Analisis scatter plot menunjukkan tidak terdapat hubungan linear kuat antara frekuensi dan total belanja. K-Means menghasilkan tiga segmen: Low Value, Medium Value, dan High Value Customer. Penelitian ini menghasilkan rekomendasi strategi bisnis berbasis data untuk CRM, digital marketing, dan manajemen stok yang dapat diadopsi UMKM.
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